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While most recent breakthroughs in scientific research rely on complex simulations carried out in large-scale supercomputers, the power draft and energy spent for this purpose is increasingly becoming a limiting factor to this trend. In this paper, we provide an overview of the current status in energy-efficient scientific computing by reviewing different technologies used to monitor power draft as well as power- and energy-saving mechanisms available in commodity hardware. For the particular domain of sparse linear algebra, we analyse the energy efficiency of a broad collection of hardware architectures and investigate how algorithmic and implementation modifications can improve the energy performance of sparse linear system solvers, without negatively impacting their performance.
1. Introduction
Linear algebra has been at the heart of the biannual Top500 (the Top500 List, http://www.top500.org/.) and Green500 (the Green 500 List, http://www.green500.org/.) rankings of supercomputers since their respective inception in 1993 and 2005. In particular, the Top500 list classifies computers according to their raw performance (in terms of GFLOPS, or millions of floating-point arithmetic operations per second) when solving a linear system of equations via the LU factorization.1 As a response to the increasing concern about the energy draw by high performance computing (HPC) facilities, the scientific computing community has welcomed the Green500 list, which puts the emphasis on power efficiency by using a performance–power ratio rather than using raw performance (concretely, the GFLOPS/W), where the performance is again based on the aforementioned HPL benchmark.
The egregious benefits that current petascale applications deliver, and those that are expected from the problems to be tackled in the upcoming exascale decade [1–4], motivate the construction of enormous and complex HPC systems. If we extrapolate the technologies underlying the current no. 1 in the Top500 and Green500 lists to build an exascale machine, the outcomes are systems that would dissipate 408 and 312 MW, respectively.
While HPL has long been criticized for not representing the actual performance of the applications currently running on HPC systems, the importance of linear algebra is far beyond just being at the base of this benchmark or modern candidates to replace it [5]. Indeed, the solution of dense and sparse linear systems is ubiquitous in scientific computing, being at the bottom of the 'food chain' for many computational applications. Therefore, any effort towards improving the performance and energy efficiency of this type of operation will surely have a strong positive impact on the countless numerical simulations that build upon them.
In this paper, we first provide a general overview of current research and developments on energy-aware HPC by reviewing software- and hardware-based power and energy evaluation methods, metrics used for quantifying the resource efficiency of numerical algorithms, and power-saving mechanisms integrated into hardware. We then specifically focus on sparse linear algebra, comparing the efficiency of different system architectures when solving sparse systems of linear equations using the conjugate gradient (CG) method, and then showing how to improve the energy efficiency of sparse linear system solvers based on this method on multicore and manycore architectures.
2. Energy-efficient computing
In everyday usage, there is often an inadequate distinction between the terms 'power' and 'energy', though the physical difference is significant. In particular, energy is the integral of power over time and, therefore, energy measures the amount of 'work' necessary to perform a task, whereas power is the rate at which work is performed and, therefore, the rate at which energy is used.
When talking about the resource demand of HPC facilities especially, the fundamental difference between power optimization and energy optimization is neglected. The term power optimization refers to adapting the power draft of the system running a specific application to some desired value, given, for example, by an upper bound or smooth transition between different values. These restrictions are in most cases motivated by the infrastructure.
When optimizing the system/application combination with respect to energy, the aim is instead to decrease the product of time and (average) power, which can be achieved by reducing execution time, diminishing average power draft or a combination of both. Thus, in some cases, it may be possible to attain a lower energy utilization at the expense of a higher power draft, or vice versa.
(a) Power metrics
As infrastructure or user demands may impose restrictions on the power draft, new metrics accounting for the key factors of runtime, power draft and total energy consumption of a system/application combination are essential for optimization. While GFLOPS/W is the de facto standard to measure the energy efficiency of a computing system (the Green 500 List, http://www.green500.org/; the Top500 List, http://www.top500.org/), recent work [6] provides strong evidence that this metric tends to promote power-hungry algorithms that deliver high sustained performance, when, in reality, the objective should be the reduction of the total energy, preferably along with the minimization of the time-to-solution (TTS).
To avoid this effect, one can rely on the energy-delay product (EDP) [7], which combines both factors, TTS and energy, into a single figure of merit, thus promoting algorithms that are more power-friendly. The FFTSE [6] progresses further along this line by considering the product between the energy and a function f of TTS. Different cost functions for f thus lead to distinct cases: f(t)=1, with t=TTS, renders FTTSE as simply equivalent to the energy, whereas FTTSE is analogous to EDP when f(t)=t. More interestingly, the linear model f(t)=α⋅t, with α a scalar, allows one to weight (penalize) for time increases; and the exponential case f(t)=eα(t−τ) exerts a stronger pressure when the TTS exceeds a certain threshold τ.
(b) Technologies for power measurement
A common approach to measuring power and energy consumption is to leverage a hardware device, in general a wattmeter, connected between the electric power outlet and the power supply unit (PSU) of the system. Alternatively, the measurement point can be inside the system itself, connecting the hardware device to the lines that run from the PSU to the different components (motherboard, disk, network card, etc.). These power measurement devices can be mainly classified according to four criteria: nature, location (internal or external, as we just observed), accuracy and sampling rate.
Nature: some devices measure the active power, that is, average power consumption obtained from the energy measured during a second, whereas other devices instead provide the instantaneous electric power that is obtained by testing the current and voltage of the machine.
Location: the point of measurement has significant consequences. Internal supervision cards measure power consumption inside the machine (i.e. downstream from the PSU) unlike other devices which sample externally (upstream of the PSU). This implies that power measurements from such internal cards refer to direct current (DC) power and do not take into account the power wasted by the PSU. By contrast, external devices measure the overall alternating current (AC) power, and therefore include the PSU inefficiencies, which can represent a non-negligible portion of the total consumption of the machine. On the other hand, the external power meters, in general, operate at a lower sampling rate than their internal counterparts.
Accuracy and sampling rate: the variability of these two dimensions can be large: from devices that offer a measurement uncertainty of ±7 W and/or a sampling rate of 1 Hz (sample per second)—in general too large to capture power variations of few watts and/or a few seconds—to extremely accurate, though in general highly expensive, elements with error margins below ±0.1 W and sampling rates in the range 10 kHz and above.
Recent processor technologies are increasingly equipped with diverse types of counters that provide power measurements, either extracted from real data or estimated via a model. This is the case, for example, of the running average power limit (RAPL) model, available in the Intel Sandy Bridge microarchitecture; the NVIDIA management library (NVML) for graphics processors; and the thermal power management device (TPMD) and the automated measurement of systems for temperature and energy reporting (Amester) for IBM's Power 7 processors. Unfortunately, these technologies can be leveraged to measure only the power consumed by the processors, not the whole machine. Moreover, in some cases (e.g. RAPL), this is an intrusive solution as it is necessary to access the energy counters via a daemon program running on the same machine that is monitored, thus introducing unwanted noise into the measurement process.
The general conclusions from El Mehdi Diouri et al. [8] indicate that, thanks to their high sample rate, the internal measurement devices allow for better identification of some power fluctuations that the external wattmeters are not able to capture. However, a high sample rate is not always necessary to understand the evolution of the power consumption during the execution of a benchmark. Moreover, monitoring very large-scale distributed systems with internal wattmeters is not practicable, as the integration of those is usually not only expensive but also very difficult. For these reasons, other sources such as RAPL, NVML or TPMD are becoming very appealing for monitoring purposes.
(c) Software for power measurement
An excellent survey on hardware and software for power profiling is given in [9]. Focusing on the software tools, PowerPack [10] is able to identify which lines feed different components such as disks, memory, network interface controllers, processors, etc. This information is then offered to the user who can gain insights on where and how applications consume power. PowerPack uses a user-friendly interface, and targets applications running on single-node platforms, though PowerPack's information can be 'manually' aggregated for parallel message passing interface (MPI) applications.
HDTrace [11] is a package to trace and simulate the power–performance footprint of MPI programs on a cluster. This software supports MPICH2 and the parallel virtual file system. Recently, it has also been extended to identify power hot spots in these applications, using information from commercial AC wattmeters.
pmlib [12] is a framework of tools used to analyse the power dissipation and the energy consumption of parallel MPI and/or multi-threaded scientific applications that comprise (i) a simple API (application programing interface) to interact with a number of power measurement devices, (ii) a library and a collection of drivers to capture the power dissipated during the execution of an application in a separate system, and (iii) an interface with integrated Extrae+Paraver packages (the Paraver Project, http://www.bsc.es/plantillaA.php?cat_id=485.) that permits an interactive analysis of a graphical trace, relating the power dissipation per node/core to information on the core activity.
(d) Energy-efficient processor technology
Current processor technology uses tools and mechanisms originally designed for embedded systems and the mobile market to use energy more efficiently. As of today, most processors adhere to the advanced configuration and power interface (ACPI) standard [13], which defines a collection of states the system can be set to depending on the workload, and thus offers a tool to tune the power usage to the current needs.
From the processor point of view, ACPI defines the so-called performance states (or P-states), which define the operating voltage–frequency pair of the processor. Vendors customize their products to feature a varying number of P-states, depending on the type of application. Additionally, in some cases, the P-state can only be set for all cores in the socket, whereas others permit each core to operate in a different P-state. In the past few years, the cost and latency of transitioning between P-states has been decreasing, and the management of the P-states has been incorporated into the operating systems (e.g. via Linux governors). State P0 corresponds to the highest voltage–frequency pair and, therefore, the most power-consuming state. Subsequent states are enumerated as P1, P2, etc.
ACPI includes an additional energy-saving mechanism in the form of the processor or CPU power states (C-states). This tool defines how and when certain processor components can be switched off to improve energy conservation. In state C0, the processor is active. In 'deeper' states (C1, C1E, C2 and so on) the clock signal is shut down to certain components (e.g. the floating-point units or certain levels in the cache hierarchy). Thus, a deeper C-state can potentially yield higher energy savings, but the latency to transition to the active C0 state will also be longer. While the P-states can be operated by the user (e.g. via utilities such as cpufreq), for security, the C-states are only accessible to the hardware and the operating system. In this sense, the only possibility for the programmer to interact with these states is by setting the appropriate conditions in the application so that the operating system can promote the processor, when idle, to an energy efficient C-state. Section 3 offers two relevant examples of this.
3. Energy-efficient solution of sparse linear systems
(a) Preliminaries
Sparse linear algebra is in many cases characterized by the solution of linear equations with sparse coefficient matrices. For this purpose, iterative methods are often preferred to direct solvers as they usually provide high accuracy solution approximations with a significantly lower computational effort [14,15]. Although a large variety of iterative methods exist, those based on Krylov subspaces2 have shown superior performance for many applications, therefore becoming the de facto standard in many sparse linear algebra software libraries.
The CG method, introduced by Hestenes & Stiefel in 1952 [15], is among the most effective Krylov subspace solvers for symmetric positive definite (SPD) systems. As all experiments in this section will be based on this method, we shortly recall the algorithm and its main characteristics next. For a linear system Ax=b, where is an SPD coefficient matrix, contains the independent terms and is the solution, the method is algorithmically formulated in figure 1, where the user-defined parameters maxres and maxiter set upper bounds, respectively, on the relative residual for the computed approximation to the solution xk and the maximum number of iterations.
In practical applications, the computational cost of the CG method is dominated by the matrix–vector multiplication zk:=Adk. Given a sparse matrix A with nz non-zero entries, this operation roughly requires 2nz floating-point arithmetic operations (flops). Additionally, the loop body contains several vector operations (for the updates of xk+1, rk+1, dk+1 and the computation of ρk and βk+1) that cost O(n) flops each. A detailed derivation of the CG method can be found in [16], including a broad convergence analysis.
In the following sections, we apply this algorithm to generate a solution approximation to different linear systems where the SPD coefficient matrices are either chosen from the University of Florida Matrix Collection (UFMC),3 corresponding to finite-element discretizations of several structural problems arising in mechanics, or derived from a finite difference discretization of the three-dimensional Laplace problem. A few key parameters from these matrices are collected in table 1 while sparsity plots can be found online.2 In all cases, the vector of independent terms b is initialized so that all the entries of the solution vector x equal 1, and the CG iteration is started with the initial guess x0≡0.
All experiments (except for those in §3c) were performed using IEEE single-precision (SP) arithmetic. While the use of double-precision (DP) arithmetic is in general mandatory for the solution of sparse linear systems, in [17] it is shown how the use of mixed SP–DP arithmetic, in combination with iterative refinement, leads to improved execution time and energy consumption for GPU-accelerated solver-platforms. The underlying idea of a hybrid SP–DP solver, with iterative refinement, is visualized in figure 2 as an iterative process where the DP solution approximation is updated by the solution of an error correction equation based on the residual and solved in SP. Note that a major conclusion from [17] is that, with this kind of solver, the impact on the global execution time and energy consumption by the parts that are performed in DP arithmetic is negligible. Therefore, it is natural to study the cost of the SP solver. Unfortunately, there exists only a DP version of the solver evaluated in §3c so that, for those experiments, we had to rely on the more conventional DP arithmetic.
(b) Time–power–energy trade-offs
(i) General overview
Sparse linear algebra in general, and sparse linear system solvers in particular, are characterized by a high number of memory accesses compared with a low number of flops. Therefore, for many computing systems, the actual sustained performance peak that can be attained in a given platform is dictated by the bandwidth between the computational units and the level of the memory where the data resides. Hardware designs often try to account for this issue by either providing sophisticated memory hierarchies consisting of multiple cache levels, and/or data streaming mechanisms, such as those in GPUs [21].
Aiming for higher energy efficiency, many multicore systems allow for modification of the core clock rate (via the P-states). Although decreasing operating frequency for memory-bound operations may, in principle, yield lower energy usage while preserving performance, this is not true for all architectures, as processor frequency and memory throughput rate are sometimes coupled. Decreasing the number of working cores on multicore platforms (thus enabling the idle hardware to transition to a sleep C-state) may have a similar effect: if the memory bandwidth is independent of the number of active cores, for this type of computations, we may be able to decrease the power draft without impacting performance by deactivating a subset of the cores.
In summary, the key factor that determines the energy efficiency for sparse linear algebra applications is the underlying paradigm concerning the hardware complexity. An architecture composed of a few complex cores, featuring high clock frequencies and deep cache hierarchies, provides high floating-point performance and greatly benefits from data locality, at the price of a high power draft. On the other hand, a low-power processor consisting of simple cores and an unsophisticated memory hierarchy, operating at moderate frequencies, aims for a lower power draft at the expense of extended execution time. Both paradigms, though, have to compete with the data-streaming approach taken by the manycore GPUs.
(ii) Experimental analysis
Next, we summarize the key results and observations of our energy efficiency evaluation of the CG method for the solution of sparse linear equation systems on several architectures representative of today's HPC landscape [22]. Following a recent approach that aims at designing an exascale architecture from low-power and embedded components (the Mont Blanc Project, http://montblanc-project.eu), we included several low-power processors in the comparison. One crucial challenge in conducting a fair comparison is choosing an appropriate level of hardware-dependent optimizations to the code as, for example, different systems usually benefit from distinct layouts of the data structures. In particular, data-streaming hardware usually exhibits significant performance increases for coalesced memory access patterns. To account for this issue, we adopt the ELLPACK sparse matrix storage format for GPU systems, while we rely on the standard compressed sparse row (CSR) format for the multicore architectures [23,24]. More details on the implementation of the sparse matrix–vector (SpMV) kernels underlying the CG method, for the CSR and ELLPACKT formats, can be found in [22].
In the following experiments, we execute 1000 iterations of the CG solver on the systems listed along with their characteristics in table 2, for the subset of the UFMC test matrices introduced in table 1, which fit in the main memory of all architectures (bmw, crank and F1), as well as the Laplace A159 matrix. All power measurements are collected using a WattsUp?Pro wattmeter. In figure 3, we report the performance (figure 3a,c) and energy efficiency (figure 3b,d) for the different test platforms when optimizing the operating frequency for either runtime performance (figure 3a,b) or energy efficiency (figure 3c,d).
Optimization with respect to time. In terms of runtime performance, the Tesla K20 (kep) and the Tesla C2050 (fer) are superior to all other architectures by almost by an order of magnitude (see figure 3a). However, the performance of these two GPU-based systems strongly depends on the matrix sparsity pattern, a sensitivity that is also shared by the Quadro 1000M (qdr), which outperforms the C6678 DSP (tic) only for those cases where the use of the ELLPACK format does not incur significant overhead on the GPUs. While tic shows some variation on performance as well as the performance-per-watt ratio depending on the matrix structure, its energy efficiency is unmatched by any other architecture. The two other low-power processors, arm and Atom (iat), show better ratios than the conventional general-purpose processors (Interlagos ail, Magny-Cours amc, Nehalem inh, and Sandy-Bridge isb), but only for some matrix cases do they show higher energy efficiency than the GPUs. For fer and qdr, it is interesting to note that, although they yield very different performance, their performance-per-watt ratios are almost equal [22].
Optimization with respect to the net energy efficiency. If we optimize the configurations with respect to energy consumption, it is, in many cases, beneficial to reduce the operating voltage and frequency. Particularly, significant improvements can be observed for the low-power processors as these architectures provide not only higher optimization potential, but also exhibit superior energy efficiency compared with the conventional general-purpose CPUs or GPUs [22]. Again, the tic exhibits the best energy efficiency, followed by arm, with the latter still superior to the GPUs or the general-purpose CPUs (see figure 3d). iat is, in terms of energy efficiency, competitive with the fer and qdr GPU-based systems. Unfortunately, the decreased voltage and frequency, which results in the superior energy efficiency, also incurs an extended run time as the reduced watt-per-iteration values for tic, arm and iat come at the price of significantly higher execution times; see the performance decrease from figure 3a,b to figure 3c,d.
(c) Leveraging the CPU states on manycore systems
The results in §3b illustrate that GPUs are among the most energy-efficient hardware architectures for sparse linear algebra. Despite the fact that these hardware accelerators rarely offer any user-controlled power-saving mechanism, their vast number of floating-point arithmetic units, in combination with an outstanding bandwidth to memory and a data-streaming architecture, results in highly favourable performance/watt ratios. However, as GPUs cannot be used as stand-alone systems, one also has to take the power draft of the host into account. In the end, the energy efficiency depends on the performance/watt ratio of the GPU and the question becomes how to save power for the host.
In this section, we show how to leverage the CPU states in order to improve the energy balance of a GPU-based iterative solver. For this purpose, we evaluate different implementations of the CG method on a platform equipped with both a multicore processor and a GPU. First, we consider a straightforward CG-CUBLAS implementation that consists of individual routines that are either taken from the CUBLAS library or self-written kernels, reflecting specific numerical operations of the method (compare the left-hand side implementation in figure 5 with algorithm 1). This natural approach has not only the advantage of the clear representation of the mathematical description of the method, but also provides the possibility of replacing individual kernels for alternative codes, and, for these reasons, will later be used as a reference implementation.
One major disadvantage of this initial implementation becomes obvious when monitoring the power draft of the CPU, which is in charge of launching the GPU kernels for the vector- and matrix–vector operations. Counter to what one might expect, the CPU does not enter a power-efficient state during idle periods, but instead remains in a power-oblivious polling loop waiting for the GPU kernel to finish. In past work, we leveraged an idle-wait approach [25] to avoid this behaviour, though the same effect can be achieved by running the code in the CUDA blocking mode, which suspends the CPU thread when waiting for the GPU to finish a task. While the suspended threads of the CPU can now be promoted by the hardware into an inactive power-friendly C-state, e.g. C1 (halt) or deeper [13], the reactivation cost may cause some runtime overhead; see figure 4, which illustrates the power benefits and runtime overhead of the blocking mode for the CG-CUBLAS implementation applied to the audi test matrix. Hence, the generally superior power efficiency of the CUDA blocking mode comes along with a certain price in terms of performance, which may negatively affect energy consumption. As the runtime is, in general, regarded as the crucial figure, the challenge is thus to recover the performance of the polling mode while leveraging the power-saving mechanisms embedded in the hardware by operating in blocking mode. The key to this lies in developing a new implementation of the CG method that breaks down the rigid structure of the original code, so that several kernels can be gathered and merged together, with the result offering a higher computational intensity.
Let us reconsider the loop of the original CG-CUBLAS implementation, in the left-hand side of figure 5, corresponding to algorithm 1. We can observe that the loop body comprises a number of calls to CUBLAS kernels inside a loop that can be potentially invoked from hundreds to thousands of times. This large number of kernel calls and the frequent data transfers between GPU and main memory are major sources of overhead. Reducing the number of calls by merging kernels and avoiding synchronization owing to data transfers are both crucial to alleviating the time overhead, but can also render a lower number of activations of the CPU, yielding a more efficient usage of the C-states and, consequently, improved energy efficiency. (We note that this technique can be applied not only to the CG method but, in general, the same approach can be applied in many other codes that off-load most of the computations to the accelerator as a sequence of short GPU kernels.)
In [26], we describe how to decrease the kernel count by gathering multiple operations into a single GPU kernel, and how to reduce the host-device communication by keeping the outcome from reduction operations on the GPU. The resulting implementation, hereafter referred to as 'merge', is shown in the right-hand side of figure 5. An enhanced version, 'merge-s', that checks the convergence criterion not every single but every s iterations of the CG loop, is also proposed in [26]. While, on average, this technique incurs s/2 additional iterations of the solver, it will also decrease the transfers from GPU to main memory as (11/s) of the transfers/synchronization are economized.
The benefits of the modifications visualized in figure 5 are summarized in figure 6 for all test matrices listed in table 1, showing the average variation of runtime (figure 6a) and CPU energy (figure 6b) in polling mode (left) and blocking mode (right), with respect to the CG-CUBLAS reference implementation running in polling mode. The target platform for this experiment was equipped with an Intel Core i7-3770K (four cores at 3.5 GHz) and 16 GB of RAM, connected to an NVIDIA GeForce GTX480 'Fermi' GPU. Power was measured using an internal DC wattmeter connected to the 12 V lines that run from the PSU to the motherboard. For further details about the experiment set-up and the results, see [26].
Concerning the performance objective, we deduce from the left-hand side of figure 6a that the merged implementations running in polling mode outperform the reference polling-CUBLAS implementation. The blocking mode may still have a negative impact on the execution time, and in the worst case we observe an increase of about 10%. However, this only occurs for very specific cases where the time for the matrix and vector operations is short compared with the cost of reactivating CPU cores, whereas, on average, the performance of the reference CUBLAS implementation can be matched. When the blocking-merge implementation is slower than the polling-CUBLAS code, shifting to blocking-merge-10 compensates for this, making the difference negligible. In all cases, the blocking-merge-10 implementation exhibits higher performance gains with respect to the reference than the blocking-merge code. In summary, figure 6a demonstrates that the performance goal is fulfilled as the merge-10 implementation in blocking mode matches or even outperforms CG-CUBLAS in polling mode.
Figure 6b illustrates the CPU energy consumption of the merged implementations, compared against those of the CG-CUBLAS code. While the merged variants executed in polling mode (left-hand side) may, on average, render some appealing savings owing to the reduced execution time, the clear winners are the same variants operating in blocking mode (right-hand side), which yield a reduction of the CPU energy draft of about 25–30%. Hence, the reformulated CG meets the twofold goal of rendering a significant reduction of the total energy consumption while retaining the runtime performance.
(d) Leveraging the CPU states on multicore systems
Here, we revisit the solution of sparse linear systems via ILUPACK (incomplete LU package4), a numerical software based on Krylov iterative methods. The package implements multilevel ILU preconditioners for general, symmetric indefinite and Hermitian positive definite systems, in combination with inverse-based ILUs and Krylov subspace solvers.
The parallelization of ILUPACK is analysed in [27], where the task concurrency intrinsic to the preconditioned iterative solution of the sparse linear systems is efficiently exploited on multicore architectures. Specifically, in this approach, parallelism is exposed by means of nested dissection applied to the adjacency graph representing the non-zero connectivity of the sparse coefficient matrix of the linear system. By recursively splitting this graph, the result is a hierarchy of independent subgraphs that is highly amenable to parallelization.
This type of concurrency can be expressed as a (directed) task dependency tree, where nodes represent concurrent tasks and arcs specify dependencies among them. The parallel execution of this tree on multicore processors is then orchestrated by a runtime which dynamically maps tasks to threads (cores) in order to improve load balance requirements during the computation of the ILU preconditioner and the subsequent solution of the triangular linear systems.
From the implementation point of view, the runtime keeps a shared queue of ready tasks (i.e. tasks with their dependencies fulfilled), which is initialized with the tasks corresponding to the independent subgraphs (leaves of the tree). Processor threads update this queue as they complete the execution of tasks allocated to them. The access to shared data structures is carefully controlled via low-cost synchronization primitives.
In the following, we evaluate the exploitation of the C-states made by two implementations of the runtime underlying ILUPACK. For this purpose, we use a scalable SPD sparse linear system of dimension n=N3, resulting from the finite difference discretization of the partial differential equation −Δu=f in a three-dimensional unit cube Ω=[0,1]3, with Dirichlet boundary conditions u=g on ∂Ω, using a uniform mesh of size h=1/(N+1). We set N=252, which yields a linear system with about 16×106 unknowns and 111×106 non-zero entries in the coefficient matrix. The tests reported next were performed using IEEE DP arithmetic. The target server contains a single AMD Opteron 6128 processor (eight cores) and 24 GB of RAM. This processor features three operating or C-states (C0, C1 and C1E). Samples were collected in this case using an internal wattmeter. Unfortunately, there exists no version of ILUPACK using SP computations, so we have to use DP for the experiments in this section.
In the previous paragraphs, we exposed how the task-parallel calculation of the preconditioner in ILUPACK is organized as a binary tree and bottom-up dependencies. The subsequent iterative process basically requires the solution of two triangular linear systems per iteration, with tasks that are also organized as binary task trees, but with bottom-up (lower triangular system) or top-down (upper triangular system) dependencies. When these tasks are dynamically mapped to a multicore platform by the runtime, the execution can be expected to exhibit a number of time periods during which certain cores are idle, depending on the number of tasks of the tree, their computational complexity, the number of cores of the system, etc. As in the previous case, where we outsourced computations to the accelerator (see §3c), it is basically these idle periods that we could expect the operating system to leverage, by promoting the corresponding cores into a power-saving C-state (sleep mode).
In the original runtime underlying ILUPACK, upon encountering no tasks ready to be executed, 'idle' threads simply perform a 'busy-wait' (polling) on a condition variable, until a new task is available. This strategy prevents the operating system from promoting the associated cores into a power-saving C-state, because the threads are not idle but doing useless work by actively waiting for tasks.
As an alternative to the power-hungry strategy, a power-aware version of the runtime underlying ILUPACK can apply an 'idle-wait' (blocking) whenever a thread does not encounter a task ready for execution and, thus, becomes inactive. Note that, as previously mentioned in §2d, setting the necessary conditions for the operating system to promote the cores into a power-saving C-state is all we can do, as we cannot explicitly enforce the transition from the user side.
The question is whether the use of the power-aware runtime comes with a performance penalty which masks the energy benefits. Table 3 compares the two runtimes, showing that this is not the case for both the computation of the preconditioner and iterative solution. Indeed, for a negligible increase in the total execution time, from 286.28 to 287.91 s, we observe reductions in the (average) power from 240.17 to 227.16 W for the preconditioner; and from 269.27 to 230.80 W for the solver. The outcome is a more than 10% decrease of the total energy from 75 163.74 to 67 758.84 J.
4. Concluding remarks
In this paper, we have reviewed the current status in energy-efficient HPC, focusing the analysis in the particular domain of sparse linear algebra. Specifically, we have experimentally compared different architectures using the solution of sparse linear systems via the CG method as the key benchmark. Furthermore, we have identified current challenges that stand in the path to effectively lower energy utilization, and we have also assessed the potential of energy-aware implementations. One key observation of our studies is that the energy efficiency of linear system solvers can be improved, without impacting runtime performance, by carefully adapting the algorithm's implementation to the target hardware. Doing so allows for better exploitation of the hardware-featured power-saving techniques. As a more general conclusion of this work, we believe that, in the context of the energy challenge of exascale computing, hand-in-hand development of computing architectures and simulation algorithms is crucial for achieving efficient resource utilization.
Enrique S. Quintana-Ortí was supported by project CICYT TIN2011-23283 of the Ministerio de Ciencia e Innovación and FEDER and the EU Project FP7 318793 'EXA2Green'. This work summarizes some key insights gained from a collaboration during the last few years. We thank the long list of colleagues that were involved in this cooperation.
One contribution of 14 to a Theme Issue 'Stochastic modelling and energy-efficient computing for weather and climate prediction'.
↵1 High Performance Linpack (HPL, http://www.netlib.org/benchmark/hpl/).
↵2 While, in principle, Krylov subspace methods belong to the class of direct solvers, as they approximate the solution in a subspace expanded in every iteration by an additional search direction until the complete space is generated, they are almost always used as iterative solvers providing a very good approximation of the solution after a few iterations.
- © 2014 The Author(s) Published by the Royal Society. All rights reserved.


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Number №1, 2013
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|Pushkar' D.Yu., Zhivov A.V., Ismailov M-R.M., Bagaudinov M.R.
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|Popkov V.M., Spirin P.V., Blyumberg B.I., Mescheryakova E.A.
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|Tyuzikov I.A., Grekov E.A., Kalinchenko S.Yu., Martov A.G.
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|Holodnyy V.A.
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|Vinogradov I.V., Sadakova I.V.
|The influence of phosphodiesterase type 5 inhibitors on the human spermatozoids motility in vitro experiment
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|New method of glanuloplasty in patients with hypospadias
|Rudin Yu.E., Maruhnenko D.V., Garmanova T.N., Sayedov K.M.

subset: commoncrawl


text:
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River Moon posted a topic in Creative NonfictionI. The first time you notice, you are pressed against him on the couch. The two of you hold a single controller between you, him with the left half and you with the right. You're playing Mario Kart with your friends, and neither of you expects to do well. He is steering, and all you have to do is hold down the "go" button, but you're sure your bad luck will carry over regardless. Miraculously, you do well, managing even to beat some of your friends. He high-fives you, giddy with your success, and the two of you are grinning like idiots. You watch him light-heartedly taunt your friends, and something in your chest stirs. Oh, you think. Oh no. II. It's nearly midnight by the time you pile into the rickety Honda. With all five of you in the car, the suspension swings dangerously to the right every time you go over a bump. The parking lot of the 24-hour McDonald's is all but empty as you pull up to the drive-through menu. You order three 20-piece servings of chicken nuggets and two large fries. As you drive to the pick-up window, he turns to you, eyes wide with fear and awe. "That's so many nuggets." "Yeah," you say. "60 nuggets." "60 nuggets. That's like a whole chicken!" You smile at him and take the bag that the employee is holding out to you. Back at the apartment, someone suggests watching The Room. It's a terrible idea and you all know it, but you put it on anyways. You're sitting closer to him than is strictly necessary, but no one seems to notice or care. You let yourself enjoy his warmth and the way his arm presses against yours. His scent is intoxicating, a mix of soap and something warm. Maybe you imagine it, but you think you feel him leaning into you, and it's all you can focus on. The movie is awful, with bad writing and worse acting, but you all enjoy laughing at the characters and plot holes and endlessly cyclical storyline. At some point, you end up leaning against him. You rest your head on his shoulder and he leans his head against yours. You stay there for the rest of the night and pray no one else can hear the way your heart is fluttering against your ribs. III. You meet at a restaurant on a Wednesday, ostensibly to work on a project. He's already at a table when you get there, so you join him. The restaurant is loud and crowded, but he's found a little high-top near the back. As you sit down across from him, the ambient music and the voices of the other people seem to fade out, and all you can focus on is him. You had always thought people were exaggerating when they said something like that, but now you believe it. The two of you compare what you've got so far, and try to be productive, but a comment he makes reminds you of a story that you have to tell him. Suddenly an hour has passed and you've made no progress at all. Despite the impending deadline and your struggles with one-on-one conversations, there's a lightness in your chest that wasn't there when you left your room. He has a class and you have to study, so you agree to meet later. You can feel yourself smiling ridiculously your whole walk home, but you can't bring yourself to care. IV. You tell your friend about him because you just can't stand to keep it to yourself any longer. It still scares you to say it out loud, so you tell them over text instead of during your Skype call. You tell them about your text conversations with him, about how he stops what he's doing to send you pictures of animals he sees, about how you're still ridiculously awkward talking to him. Their smile comes through in the emojis and exclamation marks that litter their texts, and you realize how lucky you are to have a friend like them. You're not sure if you wanted advice or just someone to listen to you talk about your crush, but the conversation reassures you nonetheless. V. The four of you link hands, forming a chain so as not to lose each other on your way out of the concert. You're at the end, clinging to his hand against the press of the crowd. Once you reach the parking lot, he holds on for an extra moment, so short you think you might have imagined it. You slide into the back seat of the car and he sits across from you. When you're not looking, he takes your hand in his again and squeezes. You turn to look at him and he's staring at you, a soft smile on his lips. In the front seat, your friend puts on some music that you all know, and the four of you sing along even though your voices are nearly blown after three hours of screaming. He holds your hand through the whole ride, even raising it to his lips and kissing it once. You can't believe your life is like this; you have amazing friends, you got to see one of your favorite artists live, and you're holding hands with a boy who likes you back. You think this is the happiest you've been in a while. VI. He walks you home from your friend's apartment after a long night of watching YouTube videos and playing board games. You spend much of the half hour walk in conversation, but sometimes you just let a comfortable silence rest between you. The city looks beautiful in the late-autumn night, so you take a moment at the top of the hill to pause and look out at the lights beneath you. You use the chill of the night as an excuse to step closer to him, and he doesn't move away. You continue to walk, but it isn't until you're nearly home that you work up the courage to take his hand. He smiles and squeezes your hand, and it makes you want to see him smile like that again and again. The two of you stop outside your building, not letting go even though it's time to say goodnight. You look at him, and you know he feels the same hesitant expectation that's sitting heavily on your chest. "Can I kiss you?" he asks softly, and you're sure it's the most nervous you've ever heard him sound. You just nod, unable to speak, but he moves closer anyways. It's awkward and tentative, but you can't stop smiling as you watch him leave. Your hands shake as you unlock the door and collapse onto your bed, filled with an uncontrollable giddiness. You think about his lips against yours until you fall asleep. VII. Your parents ask how you're doing. You tell them what they want to hear: I'm good, having a lot of fun, doing well in class. You don't say: I think I'm falling in love.


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Virtual Conference on Soft Skills
Uninvolved students do not learn in any particularly meaningful way, but getting students involved is hard. Participation points? Cold calls?
I rely on students' desire to be involved. When a student actually does not want to be in the classroom, or is afraid to be involved, I use different approaches than that described here. Luckily, most students want to involve themselves, and this article is about helping them do that by defining roles for them.
Defining roles for people makes it easier for them to act because it makes a lot of decisions for them already. Costume parties are easier to participate in when you can crystallize ideas for your outfit on a theme (80's dance party? Wild west? Alice in Wonderland, anyone?). Social dances with defined steps and a "lead" and "follower" are easier to do gracefully because the lead knows he's responsible for leading and the follower knows he's, well, supposed to follow! The definition of the roles takes the responsibility out of some of the participants' actions, which lowers the risk of engaging. And we want as many people engaging as we can get!
This year in my math class I experimented with a method I learned about from CPM, and I found it wildly successful. The idea is to put students into teams, give each team a powerful problem or question to chew on, and to give them the framework they need to chew on it. The roles I gave and the training I used are below.
The Facilitator
The student assigned the facilitator role is responsible for three things: reading problems or prompts aloud to the team, keeping everyone in the team involved, and keeping discussion going when it stalls out. This means the facilitator should now allow Tim to space out or Susanne to answer every question without consulting the others.
To train facilitators, I gave my students a list of phrases they could use. To include people, for example, they could try, "What do you think, Tim?" or, "Can you explain why you think that, Susanne?" To drive a conversation when it seems like everyone is stuck, they could say, "What have we tried so far?" or "Is there anything we could try a little bit differently?" or "Can we work on a different part of this problem and come back later?" We literally practiced saying these things as a class, in unison. You'll have to decide what method of practice is comfortable for you, but please do not think that students will jump right in to using phrases like this without practice, or that they already possess the skills to facilitate a meeting. Only a small percentage of adults have a solid grasp on facilitation techniques.
The Resource Manager
The resource manager in a team is the team's liaison to the outside world. If the team needs a ruler, the resource manager gets it. If the team needs to look something up, the resource manager goes to the computer or dictionary. If the team needs to ask me (the teacher) a question, the resource manager is the one to ask it. When I teach classes in team formations, I actually refuse to speak to anyone in the team except the resource manager. The students think I'm joking at first, but I do it for the same reasons I don't let them sit next to me in study hall.
The resource manager's role has a subtle but important facet: before the resource manager can use a resource, each member of the group must agree that that resource is needed. When a team wants to ask me a question, they must agree on it first, and figure out how to word it. Often, in this process, a team answers its own question, and they all learn how to answer their own questions. When they can't answer it, but do come to agreement about what to ask, they all learn how to formulate a question and narrow down the specifics required to make the answer useful. They know that I'll make them agree on every single question before I answer it, so coming up with concise questions becomes important. The resource manager's role includes orchestrating these discussions.
This role also needs training, and a list of possible phrases. "Is there a single piece of information that would help us move forward?" or, "What information do we already have?" or, "Before we ask Riley what this symbol means, what are our guesses?"
The Task Manager
The task manager's primary role is to keep track of time, make sure that the team is spending appropriate amounts of time on different parts of the assignment, and alert the others when it seems like the whole group is moving off task. This role overlaps with the facilitator quite a bit, but the concreteness of having specific target times is helpful to students and I've never felt like this role is redundant. Especially when the facilitator is busy trying to lead a stuck group, it's helpful to have a task manager to keep track of more administrative details.
As always, when expecting a certain behavior from students, we should show them what it looks like. Training task managers can look like a skit, a list of useful phrases, etc. You can emphasize the task managing you do in your class all the time – instead of saying "please take out your homework," write a schedule for the period on the board ahead of time and say, "I see that it's time to take out our homework."
The Recorder / Reporter
The recorder takes notes and creates minutes, if you will. The notes can be her own, but the minutes must be presented to the team regularly to be sure that they are fully representative of any agreements the team has come to together. These minutes are the final permanent product of the team and can be turned in so that I (the teacher) can give in-depth feedback on a team's mathematical understanding later.
The recorder is also the reporter, who may be asked to give impromptu oral reports of the team's progress to the entire class. Occasionally I ask this of a team that is understanding something fast or in more depth than the other teams, or use a quick round of reports as a closure for a class period.
The training for this role is the hardest, I think. What if you have students that don't have practice writing summaries? This year I practiced with the whole class: we would have a ten-minute discussion and then summarize it on the board, making sure we noted all of the important parts and only the important parts. Still, I was least satisfied with the work I saw from this role throughout the year.
Together, these roles give the students a powerful framework for their behavior during class. Since every student has responsibilities to every other student, disengaging becomes less desirable and also less acceptable to the students. In a large class with no specific roles, if Tim zones out it doesn't really affect anyone else, and Tim doesn't have an easy way to zone back in. With groups and specific roles and responsibility, when Tim zones out his teammates notice immediately, and can prompt him with aspects of his role to re-engage right away. So great!
These roles make me more comfortable with my guilty admission: I don't care very much if the kids learn math. I mean, I'll teach them some math, and when they leave they're going to see more of its beauty and be equipped to use it in society. But which is more important, vector addition or working in a team? Factoring or formulating questions? Integrating or leading peers? Obviously, obviously, the math comes second. It's just lucky that learning math provides so many opportunities for learning the more important things.


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Frequently Asked Questions on Mercedes-Benz R-Class
Q.1 How many colours are available in Mercedes-Benz R-Class?
Q.2 What is the boot space of Mercedes-Benz R-Class?
Q.3 What engine oil is best for my Mercedes-Benz R-Class?
Q.4 Is Mercedes-Benz R-Class available through CSD canteen?
Q.5 What is the mileage of Mercedes-Benz R-Class?
Q.6 What is onroad price of Mercedes-Benz R-Class in India?
Q.7 Does Mercedes-Benz R-Class have safety airbags?
Q.8 Is Mercedes-Benz R-Class available in diesel version in India?
Q.9 How is the performance of Mercedes-Benz R-Class?
Q.10 What are the safety features in Mercedes-Benz R-Class?
Q.11 What is the price of Mercedes-Benz R-Class in India?
Q.12 What is the difference between old Mercedes-Benz R-Class and new Mercedes-Benz R-Class?
Q.13 What is the top speed of Mercedes-Benz R-Class?
Q.14 What is the lowest price of Mercedes-Benz R-Class in India?
Q.15 What is the tyre pressure for Mercedes-Benz R-Class?
Q.16 What are the variants of Mercedes-Benz R-Class?
Q.17 What is the waiting period of Mercedes-Benz R-Class in India?
Q.18 Is LPG/CNG versions available of Mercedes-Benz R-Class in India?
Q.19 Is there an automatic transmission version available in Mercedes-Benz R-Class?
Q.20 What is the power of Mercedes-Benz R-Class?
Q.21 What is the acceleration of Mercedes-Benz R-Class?
Q.22 Does Mercedes-Benz R-Class have power steering?
Q.23 What is the mileage of Mercedes-Benz R-Class on highways and City?
Q.24 What is the fuel tank capacity of Mercedes-Benz R-Class?
Q.25 Tell me the engine specifications of Mercedes-Benz R-Class?
Q.26 What type of automatic transmission comes in Mercedes-Benz R-Class?
Q.27 Which is better Mercedes-Benz R-Class petrol or Mercedes-Benz R-Class diesel?
Q.28 What is the service and maintenance cost of Mercedes-Benz R-Class?
Q.29 Tell me about Mercedes-Benz R-Class interiors?
Mercedes-Benz R-Class Further Research
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Move to Germany, where the iPhone is dominating.
ComScore released on April 1st statistics about the mobile market share in the United States. Google's Android OS was able to gain 7% market share. It now has a 3rd of the US market. Apple's iOS is pretty much stuck at 25% on 3rd place. RIM has a bit more than Apple at 28.2% in the ComScore report.
If Android can continue this growth it will become the dominating mobile OS by the end of 2011. The only company that can stop this from happening is Apple. But Apple would need to start being more aggressive than it has been so far.
In the tablet world Apple has an easy play right now with the iPad. Nobody comes near it right now. The software, hardware and service combination at the $500 price-point is apparently too tough for the competition to beat in 2011. The smartphone market it is a different picture. At least in the US. Web analytic company webtrekk issued a mobile OS market share report for Germany that shows that Apple's iOS devices have 81.46% market share (based on online access). The iPhone has 45.26% alone compared to Android with 9.04%.
So why is the iPhone dominating the mobile phone market in Germany and not in the United States? I live in Germany and actually do not know anybody using an Android Phone. Even my open source die-hard Linux fans roll with the iPhone.
Android is also growing in Germany, but is still very far behind. Apple needs to find a way to create for the iPhone again a critical combination of software, hardware and service at a price-point the competition cannot touch. What is not helping here are rumors that Apple is not going to release a new iPhone this June. A fall release of a new iPhone makes sense though because of the intense shopping season that commences with Black Friday sales at the end of October. On the other hand Android can gain a lot of market share until Fall with new cool 4G phones and other new releases.
I am sticking with the iPhone. I am over 40 and I am done with trying things out. I have almost moved my whole gadget infrastructure to Apple in the last two years. I am waiting for a new iPhone though, as I still have a 3GS. Good thing my iPad 2 is coming soon, hopefully.
About Android Phones:
Android smartphones stumbled onto the scene in November of 2007. The first Android handset was the T-Mobile G1, released in October of 2008. Today's most popular line of Android phones is the Galaxy S from Samsung. The Nexus S is Google's current flagship Developer Phone. Although initially founded as an open-source alternative to closed ecosystems like iOS, Android has grown less open as time has gone on. Largely as a response to fragmentation and as a way to buoy the App Market.
The Android Market launched on October 22, 2008. Paid applications went live a few months later in 2009. There are now over 200,000 Android apps that have been downloaded an estimated 2.5 billion times. Unlike Apple's App Store, there are no real controls on who can put an App on the Market. This has lead to numerous malware outbreaks as well as rapid growth.
Android has been the world's leading smartphone platform since January of 2011. The most recent software release was Android 2.3/2.4, Gingerbread. The next anticipated update will be called Ice Cream and is expected to fuse Gingerbread and Honeycomb (the tablet OS) into a single OS. Release is slated for mid-2011.


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2013 CHEVROLET TAHOE LT - 4 Wheel Drive - Black with Black Leather - Ranked #1 among 2013 Affordable Large SUV`s the Chevrolet Tahoe was also the winner of the 2013 award for `Best Large SUV for the Money`. The Tahoe received positive points for a strong V8 engine and good fuel economy for the class. Consumer Guide reports ``Tahoe`s smooth drivetrains are the stars of the show. The 5.3-liter V8 engine especially is a model of refinement. Kelley Blue Book states ``With its boxed frame high-tech suspension and precise steering - plus generous sound dampening - the 2013 Chevrolet Tahoe offers a luxury-car-like riding and driving experience. Cars.com reports Hammer the gas pedal and the Tahoe can move with gusto. Cruising and passing on the highway are effortless.`` This LT model features running boards roof rack rear parking aid tow hitch tow package remote start remote power locks wood trim heated seats power seats Bose Sound System adjustable pedals three zone auto climate OnStar AUX Input satellite radio USB Input Bluetooth and steering wheel controls. This 2013 Chevrolet Tahoe offers eight passenger seating handsome styling and great towing ability! All cars for sale at our dealership are covered by a warranty and are sold Maryland State Inspected. Extended warranty packages are available for purchase on all cars. Call us today for a test drive or more information at (410) 358-9663 or email us at firstname.lastname@example.com. Our sales department is open Sunday through Friday! CarZone USA is proud to be one of the few used car dealerships in Maryland to offer a no pressure sales environment!
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|Cruise Control
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|Driver Airbag
|Driver Multi-Adjustable Power Seat
|Electronic Parking Aid
|Fog Lights
|Heated Exterior Mirror
|Heated Seats
|Interval Wipers
|Leather Seats
|Leather Steering Wheel
|Luggage Rack
|Owners Manual
|Passenger Airbag
|Passenger Multi-Adjustable Power Seat
|Power Mirrors
|Power Seats
|Power Steering
|Power Windows
|Rear Air
|Rear Defroster
|Rear Wiper
|Running Boards
|Satellite Radio
|Separate Driver/Front Passenger Climate Controls
|Side Airbags
|Side Head Curtain Airbag
|Third Row Seat
|Tilt Wheel
|Tire Pressure Monitor
|Tow Package
|Traction Control
|Trip Computer
|Vehicle Stability Control System
|3 Months of Provided Satellite Radio Service
|8-Passenger Seating
|Bose Sound System
|Oil Life Monitor
|Radio Data System (RDS)
|Rear Automatic Climate Controls
|Rear Headphone Jacks with Audio Controls (2)
|Remote Power Locks
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|Sun Sensor
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|Tow Hitch
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|USB Input
|Voice Command System


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Academic journal article The Middle East Journal
Oman: Political Development in a Changing World
Article excerpt
Oman: Political Development in a Changing World, by Carol J. Riphenburg. Westport, CT and London: Praeger Publishers, 1998. xii + 237 pages. Bibl. to p. 242. Index to p. 248. $59.95.
Reviewed by W Lynn Rigsbee 11
Praeger is to be commended for publishing Carol J. Riphenburg's Oman: Political Development in a Changing World, especially after its previous text, The Sultanate of Oman: A Twentieth Century History (New York: Praeger, 1995) by Miriam Joyce, was not well received.'
Riphenburg's work provides an insightful analysis of Omani political development since the advent of the Qabus regime. In eight chapters, she covers the issues of historical legacy, political and economic development, evolving gender equality and foreign policy.
Of particular importance is her examination of the Sultanate's evolving "democracy" within the context of Oman's political culture. This culture, which is Islamic and patriarchal, ensures that resulting institutions will be appropriate for the society.
Riphenburg shows that the Islamic components of Oman's political culture and evolving democracy are based in the Qur'anic principles of shura (consultation) and ijma' (consensus). These concepts have been used by Sultan Qabus as the justification for the establishment of the Majlis al-Shura, or Consultative Council. The members of the Majlis are elected by "nominating colleges" from each of Oman's wilayat (governorates). These colleges consist of "notables"-men and women of high standing in their community who assemble in public to nominate individuals to the Majlis. The names of nominees are then passed to the deputy prime minister of legal affairs, and, ultimately, to Sultan Qabus himself for the final selection of the Majlis membership.
Thus, the Majlis is, as the author notes, an institution based on indirect nomination and representation. As a result, it is not, in the Western sense, a democratically elected representative body. Despite this limitation, the establishment of the Majlis marks the beginning of representative government in the Sultanate. …


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Hi PhotoDudes.
Being a tech head and fancied a new toy I purchased a Nikon D3100 and now Im stuck at what all the buttons are for LOL
Any tips for this specific toy.
Took these today for starters.
Three pics of some of my fish in my marine tank.


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London Event: What Photo Buyers Want from Photographers
One of our top goals at PhotoShelter is to provide photographers with the information and insights they need to successfully communicate with photo buyers, so that they can grow their photography businesses and get hired.
So we're excited to announce that we're teaming up with IdeasTap and Blurb in London this May for an exciting panel discussion on "What Photo Buyers Want from Photographers". The event is free and takes place in London on May 17, 2012.
With large communication gaps between photographers and their commercial and editorial clients, we will break down these barriers to provide photographers with tips and insights straight from the source to help grow their business better than ever before. Specific tpoics will include:
- The best way a photographer can promote their work to a buyer.
- What makes a great website.
- The personal characteristics of photographers that buyers seek.
- And much more!
PhotoShelter's Allen Murabayashi and Blurb's Rachel Stanley will speak on additional ways to improve your business. The panel will also include speakers from GQ, Q Magazine, and more.
Join us for a drink and a panel discussion on May 17th from 6.00-8.30-pm at IdeasTap's headquarters in London. The event is free and open to the public. These sessions are very popular and get booked up quickly, so don't delay in signing up for your free ticket.
IdeasTap is a not-for-profit organisation that funds, connects and nurtures new creative talent. It was launched in December 2008 as the arts platform of The Peter De Haan Charitable Trust.
Blurb is a company and a community that believes passionately in the joy of books – reading them, making them, sharing them, and selling them. CEO & Founder Eileen Gittins will also be speaking at Luminance – PhotoShelter's photography conference this fall.


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The Monelli Memo
I sing a song of the saints of God, patient and brave and true.
Who toiled and fought and lived and died for a Lord they loved and knew….
So begins the joyful children's hymn that was part of All Saints Day worship throughout my youth. The hymn continues to reference saints who were everything from shepherdesses to queens, and doctors to priests. But the ending of the hymn was always what I liked most:
They lived not only in ages past; there are hundreds of thousands still;
the world is bright with the joyous saints who love to do Jesus' will.
You can meet them in school, or in lanes, or at sea, in church, or in trains, or in shops, or at tea;
for the saints of God are just folk like me, and I mean to be one too.
Who are the saints in your life? Who has inspired you to deeper faith? Whose life has encouraged you to serve or speak up for those in need? All Saints is the perfect time to celebrate all those who have inspired and encouraged you and to introduce them to your children. Did a great uncle introduce you to the joy of a well told Bible story? Did a friend encourage you to service when you were hesitant to take the risk?
Whether the saints in your life can be found in books or your family's photo album, take some time this month to introduce your children to these special people, to celebrate who they have been (or are) to you through pictures and stories. Then help your children to identify the saints in their lives and to share their stories with you.
For His Sake,
The Advent Event – Making Room for Jesus
Sunday, November 20 – 9:30 am
If you would like to help prepare for or help on the day of this event, please contact Nancy Monelli (email@example.com) as soon as you can.
Continuing Programs
Bread for the Journey continues to meet each Wednesday evening. Bread for the Journey is a mid-week respite for rejoicing, reflecting, and renewing with the family of faith.
Sunday School classes meet on Sundays from 10-10:50 am each week. During this time of Christian formation there are classes for all children and young people in preschool through high school.
The Phinney Phlames! The Phinney Phlames is the Youth Group for kids in 4th and 5th grade. This month the Phlames will be attending a performance of The Lion the Witch and the Wardrobe on November 6th. Reservations are required so please contact Nancy Monelli right away if you have not already done so.
Programs for Adults
The Caregiver Circle: The Caregiver Circle meets at 10am on the 3rd Sunday of every month. This month we will gather on October 16th in Pastor Hansen's office. If you care for an elderly parent, a loved one with a chronic condition, or a distant relative with continuing needs, you are welcome and encouraged to take part in this support group. This is an opportunity to meet with others experiencing similar life challenges, to learn coping skills, discover local resources, and pray with and for one another. If you would like more information, please contact Nancy Monelli at firstname.lastname@example.com.
Sacred Listening: Sacred Listening will meet on December 4 at noon in the Middle School Room.
More Bread for the Journey: Pastor Hansen will lead a Young Adult study during "Bread for the Journey" on Wednesday evenings beginning November 16 at 6:30 p.m. We will look at the scripture readings for Advent and consider what it means to prepare for Christ's coming. Anyone is welcome. (we're not restricting this to young adults). Pastor Van Kley continues to lead a lectionary discussion during this time. All adults are welcome to participate in the BFJ closing worship at 7:15.


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Cobalt Boats' 220 enjoyed tremendous popularity when it debuted as part of Cobalt's 10 Series of bowriders. Kansas-based Cobalt likens it to the estimable BMW 3 Series, high-quality boats at a more approachable price. On the 220, you still get the sweet performance that Cobalt is known for, and you get many big-boat amenities, such as the leather-wrapped steering wheel at the helm with the Cobalt insignia designed to always spin upright. The dash has the same hand-stitched brow and digital gauges you'd find throughout the Cobalt fleet.
This particular Cobalt 220 has a nice assortment of option upgrades including Arch fwd folding W/Bimini, Bow and Cockpit Tonneau covers, Depth-water and air temp package, Flip down Swim Step, and 3 color Custom Graphics Pacific Blue.
She is powered with a Mercruiser 270 HP Mpi Bravo 3 Cat Engine with only 215 Hours!
She also has extended warranty thru 7/27/18!
Mattituck Bay 631.298.4770 Mattituck Sound 631.298.4739
Southampton 631.283.6736 Port Washington 516.304.5376
Come aboard the 220, and know comfort and convenience typically found only in far larger boats. Experience a spaciousness that maximizes flexibility in your use of the boat, thanks to Free Space Reclamation (FSR), Cobalt's studied minimization of heretofore unused space. The 220 makes idealized use of every square inch of its wide and sturdy stance, the stadium seating key to the easy accommodation of a dozen guests and their gear. And the swim step, of course, Cobalt's game-changing, patented contribution to safety, convenience, and accessibility makes boarding a breeze. Memories gather naturally under the 220's aluminum wakeboard arch – simply foldable, by the way – an addition that makes your boat as athletic as it is roomy. You decide exactly how the heart-thumps should occur, on board or otherwise.
2400 Camp Mineola Road
PO Box 1409
Mattituck, NY 11952
United States


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CHAPEL HILL – Jan Boxill, UNC's Faculty Chair, said Wednesday that significant progress has been made in achieving "balance" between athletics and academics at the University. In the wake of scandals that continue to haunt Carolina, the pressure is on to make changes and prevent future indiscretions.
"We can be a model for other Division I athletic programs," Boxill said. "That doesn't mean that we will reach complete agreement among the faculty as no policy will."
In mid-July, Boxill was accused by the Raleigh News and Observer of a cover-up regarding information about UNC's athletic program
Boxill told WCHL News that she was cast in a negative light by the N&O for trying to help the University's image during tumultuous times with the NCAA, the media, and even the public. UNC faculty issued a statement supporting Boxill after the article was published.
While addressing a committee of the Board Trustees Wednesday, Boxill said that the work of the Faculty Council's athletics focus group had been tedious, but that it was on a path toward progress.
Efforts have been on-going across campus to strengthen relationships between academics and athletics. The Academic Support Program for Student-Athletes was reorganized and now reports to Dean's office.
Earlier this month, the Rawlings Panel issued a report on the role of athletics in campus life. It was commissioned by former UNC Chancellor Holden Thorp.
Boxill said that report was discussed by the Faculty Council on September 13 and will be dissected more thoroughly next month.
Chancellor Carol Folt and Provost Jim Dean both assumed their respective positions this summer. Boxill said this has given her a fresh perspective on Carolina's strengths and weaknesses.
"Their visible presence and willingness to learn from all of us has presented opportunities for the faculty to find solutions to our old and new problems," Boxill said.
Director of Athletics Bubba Cunningham, Folt, and Dean together formed the Student Athlete Academic Working Group in August.
Dean said Wednesday that the three leaders were not making just a "casual effort" to improve the connection between athletics and academics
"And this group, because of the nature of the people who are on the group, is not a group that will be making recommendations," Dean said "There is no one for us to make recommendations to. We will be making changes."
He added that he, Folt, and Cunningham were going through "everything that has to do with student athletes with a fine-toothed comb."


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In my 4th week of Body Beast I found my self losing 2 lbs eating close to 4000 calories per day, so I decided to add a few calories to my morning Shakeology. Basically I just follow the Chocolate Banana Nutter recipe but just add 1/2 cup of old fashioned oatmeal to it and grind it up first. I also eat two English muffins with almond butter and flax seed with this shake.
1/2 cup of oatmeal (grind)
1 scoop of Shakeology
1 Banana
1 Tablespoon of peanut butter
10 ounces of water
10 ounces of ice


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There's nothing like a powder day for local skiers and snowboarders.
There's nothing like a powder day for local skiers and snowboarders.
With more than a foot of snow dropped on the region in the past week, there have been several powder days, and despite Wednesday's rain, conditions aren't bad at most area ski slopes.
"When you are skiing on powder, it's just a different sensation, a different experience," says Chris Gruner, 17, of Kingston. "It's like you just fly through the air. It's always a lot more fun. I couldn't wait for those storms."
Gruner and some of his pals are taking a road trip to Vermont this weekend. Killington, Stowe, Bromley and Stratton Mountains are all possible white destinations.
Like Gruner, many will flock to the slopes this week because the Christmas break is sort of the unofficial kickoff to snowsports season. Lots of people are flush with new equipment, or they finally have some time to hone their racing skills or snowboarding tricks.
Skiers and snowboarders are crowding the hills despite the slumping economy.
"When we got that early snow last week, it was like an early Christmas present," says Amy Richardson, director of sales and service at Mount Peter in Warwick. "I'm not sure why, but it's been real packed. Even today (Friday), we got hammered. We weren't sure what to expect with this being the new Black Friday. I just think when it snows it gets more people thinking about skiing."
Adds Jessica Pezak, communications director at Hunter: "We had 18 inches, so we feel the excitement. We've had thousands and thousands of skiers (on up to as many as 44 trails) and we expect a lot more this weekend. The economy hasn't affected us. Maybe people don't want to make the leisure things the first to go. I think we've caught a lot of skiers who might be going up to Vermont or even flying out West."
Business has also spiked at Potter Brothers Ski Shop in Kingston with customers milling the store for skis, snowboards and all kinds of accesories. Kyle Potter, vice president of Potter Brothers, said he's also seen a rise in cross-country skiing and snowshoeing customers.
Back on the slopes, the fresh snow, much better than man-made stuff, makes for smoother runs and sharper turns. Gliding down the mountain on skis or pulling off a flashy move on the halfpipe is easier.
"It's so smooth, it's like surfing out there," says Gruner's identical twin brother, Ben, an avid snowboarder. "It's perfect out there, especially when you are out there with all of your friends."


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Frequent AOS Crashes under Ax32Serv!fieldExpr::sqlwhereclause
The fix makes no crash happening in this scenario.
More information
Note This is a "FAST PUBLISH" article created directly from within the Microsoft support organization. The information contained here in is provided as-is in response to emerging issues. As a result of the speed in making it available, the materials may include typographical errors and may be revised at any time without notice. See Terms of Use for other considerations.


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NBC continues to flail in last place, with new shows like Outlaw and Undercovers bombing and veterans like The Office eroding. Jace Lacob offers six possible ways to save the Peacock.NBC is in terrible shape. Once the home of such brand-defining comedies as Seinfeld, Friends, Frasier, and Cheers, it was a first-place network that created the oft-repeated catchphrase "Must See TV."
It seems like a lifetime ago.
Despite executives' huge promises of investments in scripted programming and renewed creativity, NBC's fall programming has been DOA. The network might be able to brag about Sunday Night Football, but it can't rely on the sports franchise all year for ratings. Its biggest scripted hit is Law & Order: SVU, which, in its twelfth season, is currently averaging just 9.2 million viewers. It's all downhill from there, with beloved 30 Rock—despite being named the best comedy on TV of the last decade by Newsweek—only bringing in an average of 5.7 million viewers so far this season. The Apprentice scored an insanely low 3.5 million viewers recently. NBC hasn't had a breakout hit since the days of Heroes, which the network ran into the ground until it was finally put out of its misery last season.
Read the full article at The Daily Beast →
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This page shows samples of my advertisements, collateral and writing samples. Some of the writing samples have been taken from assignments completed for my Masters degree in Integrated Marketing Communications.
Campus Recruiting Collateral
Writing Samples
- Style Guide (Created and Implemented for Employer)
- Integrated Marketing Communications Plan (Master Degree Program)
- Public Relations Campaign (Master Degree Program)


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Ofsted Praise our use of iPads
Staff and students were praised in our recent Ofsted inspection:
- Students are generally keen to learn and respond well to questions in class. They are able to sustain attention and focus on tasks, and are active in investigating topics. They are responsible when using their tablet computers, and research and check information in lessons independently.
- Teachers provide good resources for students and students have access to a personal tablet computer. Teachers use these well to enrich the curriculum and extend opportunities for independent learning and research.
- Reading is exceptionally well supported across school and is a regular feature of each day in school. The extensive literature available to all students through their personal tablets helps to ensure equal access to resources.
Staff innovation
Mr Eunson: I would like to share this excellent trailer produced for a film version of Roald Dahl's short story, The Landlady. Currently they are studying short stories in English. The Year 8 students who produced this work are Josh , Ben , Will , Georgia and . The class completed a peer assessment for each trailer. We used Apple TV to view the end products. Click on the link below to view:
Miss Main: Kahoot is fantastic:
Miss Main on Twitter: "Well done Nathan F – excellent understanding shown with @GetKahoot of the Battle of Hastings "@year7UPT http://t.co/mpqHTdRFwv"
"Well done Nathan F – excellent understanding shown with @GetKahoot of the Battle of Hastings "@year7UPT"
The students loved it and it was a great chance to tweet their achievements.
Mrs Mitchell from the Geography Department was observed by Sue Williamson, CEO of the Specialist Schools and Academies Trust (SSAT) using this fantastic app with her
Year 7 class: WunderStation brings you rapid-fire current conditions, forecasts, and historical weather data from any weather station in Weather Underground's network of over 100,000 personal weather stations. View, analyze, share and compare data from local personal weather stations with elegant, customizable graphs, infographics, animated wind direction, rainfall totals.
I have also designed an iTunes U course on rivers which can be accessed by the students on their iPads at home and in school. iTunes U provides updates and allows the students to post comments. (Double click on the image below to make it bigger)
Mrs Bennett: I use an App called 123d creature to effectively engage boys. By allowing use of the app (it is a virtual kiln where students can add pattern and colour etc), students are dealing with an interface they are familiar with (virtuality). The quick and effective results they achieve on the app (used as a starter). Gives the students the confidence to move from the virtual to the physical process of making and problem solving. Below is an example of a sculpture created by a student using the said app.
Mr Collis: Use QR Codes to link to website URLs/pictures/text etc. QR Codes work really well for starters/plenary activities. Students can scan QR codes as soon as they enter the classroom. Students do not need to type in a complicated website address; the codes are very simple to scan.
- Download 'QR Reader for Ipad' from the App store.
- Use http://www.qrstuff.com/ to generate your QR code (Link from QR code).
- Add QR codes to worksheets. Alternatively, project QR codes onto your whiteboard. Students can scan them.
Dr Rees uses the Mangahigh website to differentiate at all levels: https://www.mangahigh.com/en-gb/
Mr Biard: Map Draw,a free i-pad app. Students can plot their journey to school either on map or satellite image. The app tells them the distance. They can also measure the time it takes. This data, relevant and real, can be used to make frequency tables of distances travelled to school and speeds. These can be used to compare groups who walk, cycle, are driven or come by bus. See below:
iPod competition entries
Again we have a fantastic portfolio of work from years 7 and 8 with hundreds of entries, here is just a selection. iPad videos Click on the links below to watch some amazing videos produced by the students using their iPads.
By Amelia Lindop
For the love of chocolate produced by Tom , Josh s, Ben , Joe , and Will :
Sasha: The piece of work that I produced a blurb and a front cover for Al Capone Does My Shirts, our class hook at the time.
Amelia Lindop analyses a poem in English. Jemma Holton: I produced this for my Geography homework on weather phenomena. Katie Spall: I made this piece of work in art, on an app called Pic Collage. It is about Lesley Halliwell and her artwork.Liam Johnson: This work is about ways to measure different weather conditions. I really enjoyed doing this piece of work because it was creative, which I like doing on the iPad. This piece of work was complete in a geography lesson. Laura Dixon: This was from my English lesson when we were researching the Greek gods. We had to create a booklet of information. This is one part of the booklet from pic collage. This is a fact file on Hera she is the Queen of heaven; God of birth and marriage. Emily Wilson: I created this in Geography for the Nepal Earthquake and it explains what we are doing to help rise money for this.
Cally Worthington: My best piece of work. We made a poster on the Nepalese earthquake in geography.
Ben Jones used his iPad to create some detailed research on Shakespeare's plays. Daisy Saxby: My work is about the general election week and about who I would vote for if I had a chance. I enjoyed making this and following the election. Jemma Holton produced this excellent work on life in the middle ages. Monden Masaki completed a news report on Conway Castle. Tasmina Islam produced this research on Medieval England.
Millie Cowley produced this wonderful poster in RS.
And the winner is…Liam Johnson, Well done!
Upton Student ELF Group update
Upton ELF group have been extremely busy creating presentations, blogs, videos and much more over the past few months. The ELF group now have their own website that has been designed by the students. The website has all the latest news, events and information about the ELF group. You can view the site at uptonelf.weebly.com The year 7 ELF students have been working on a presentation that is currently being delivered to their year 7 form groups. The idea behind the presentation is to make year 7 students aware of the Elf group and the good work that they do as well as re-capping the rules with regards to using their iPad in school. Year 7 ELF students delivering their iPad presentation The current year 8 Elf students are working on an iBook for the new year 7 intake, September 2015. The book is being compiled with the feedback from students previously starting out with an iPad in year 7. The book will have basic 'how to' tips and instructions to help students use the iPad to its full potential. The book includes basic instruction video clips, check some of videos out here youtube https://www.youtube.com/watch?v=QE83HYxQo7c
ELF App Reviews
The ELF students have been busy trying out new apps and then posting reviews on the ELF Blog. You can view the app reviews at uptonelf.weebly.com Here are some of the latest posts; App Review
App: Maths bash secondary free Rating: 7/10 Type of App: educational Subject area: Maths Recommend/ not recommend: Recommend
How to use: There are 4 sections to this game. Once you have chosen the section you would like to play, a timer starts and you have to answer as many questions as you can. I like this App because it tests your knowledge and it helps you to learn your times tables.
Emily Year 7 student
App Review App: Four letters Rating: 9/10 Type of App: Educational How to use: This app is an literacy educational app. Four Letters is extremely fun, because you have to try and get a four letter word in a race against time. If you get the word then you carry on until you cannot get any more words. I love trying to beat my personal best on this great game! Liam Year 7 student
iPad Review- Benefits of being able to use my iPad
What I can do now, that I couldn't do then
When I first started I couldn't… – Contact teachers – Send/do homework on my iPad – Research during lessons – Use good apps to help revise and collect information – Share work with friends to help each other I have access to do all these things now I have my iPad. It is making me more confident about learning, and is building up my ICT skills. It is so much easier to contact teachers about either homework, class work, or any other things. I could either send an email to them or a comment by using an app called Showbie. Likewise, they can put comments on my work. Doing homework or any other work on this device is a lot more fun and interesting than on paper. You can be really creative with presentation on apps such as Sketchpad, Pic collage and iMovie. The thing that I find most useful is the researching tool on our iPads. During class, the iPads can enable us to research information to help us with our work. Before we had iPads, we had to use computers which was inconvenient as not every classroom has computers. Helpfully, having iPads in school means that we don't have to carry as many books around with us. By Hannah, Year 7
We won the 'Classroom of the Future' Competition
The year 7 students recently entered a competition to design a 'classroom of the future.' The competition is being run by WestCoast Apple Team and the winner will be announced on Friday 12th June. Here are some of the fantastic entries.
"My classroom allows the need for class changes to no longer be required and helps each student individually. It has the classroom has a change programme which allows the room to change depending on the subject being taught at the time, such as Science, DT, and food tech, this means that the students don't have to move classrooms and be late".
Not only that the teacher will also be holographic and be changing depending on the subjects. This way teachers don't have to move classrooms and can be interactive with the environment. If a teacher is demonstrating a practical, the items needed would be in the actual classroom. Supervising teachers will be required to do their part by keeping everyone on task. The screens are also holographic meaning that teachers can just type up a task and it'll immediately show. Student also get the technological experience and have their desk equipped with the following:
- A wide array of buttons
- Touchscreen border
- Mini flat screen monitor
- Holographic
- An anti-cheating boarder (controlled by teacher
The students will also have a holographic avatar that will help them if they're stuck. They are summoned by the push of a button. The classroom also has a leisure corner and the teacher's desk has a mischief camera to alert the teacher to any rules violated." Mubarak Adedigba, Year 7
" I think a 'Class Room of the Future' would have lots of highly advanced technology. These features include and interactive wall, Smart screen desks and robot helpers. These advanced pieces of technology would help improve the learning of the children of the future." Hannah Kelsey Year 7
For all the latest news and information follow: @Upton_ELF or Uptonelf.weebly.com


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I don't identify as a writer (such a risky, controversial lifestyle choice–what would my mother think?), but my editorial work and career path have proven to be surprisingly writing-intensive. I'm coming around to the idea, and learning–stop laughing–that writing is hard.
Now, as a professional who's supposed to be a trusted judge of writing quality, with sage advice on developing manuscripts into saleable material, I feel an enormous pressure for my own writing to be consistently brilliant, deep, and "perfect." Whether it's an article, a blog post, or a manuscript critique, I often fret and obsess long past the point where such activity serves any useful function. The pursuit of this ideal defeats the purpose of writing itself. I believe (I know) that good writing has nothing to do with "correctness," much less "perfection." Writing strives to be an art, or a representation of speech, or a vehicle for the sharing of ideas. There is no room for "right" and "wrong" in that quest. They're just distracting, enthusiasm-killing ideas.
Anyway, I get it. I get the bizarrely lost feeling of producing work with no guiding structure to conform it to, the queasy unease of arbitrarily calling it "done," or "ready," and the naked vulnerability of displaying it to someone else (indeed, to the entire internet), and I sympathize. But let's find a way to deal with it and keep working.
Your work's going to be imperfect as it first emerges from your brain, and it will always remain so, no matter how great it becomes. The trick is to find an acceptable place to stop obsessing over it and let it out into the world, where it may well be judged harshly or even, you know, mocked by former classmates. As you gain skill and experience as a writer, that place will become easier to identify and closer to what you'll define as "ready." For me, that means:
readiness, n. The state at which authorial cringes at word choice are over, and there is a minimal chance of Amazon-review postings by a miserable writer filled with regret at not recognizing a chance for a minor character to contribute more to the plot.
It is terrible to hear self-published authors complain that an older version of their book was unfairly critiqued and misunderstood, because "it's so much better now"–utterly unprofessional. Bad. Don't let that happen to you, and for the love of Whatever, don't deliver your work to an editor or reviewer to read and then interrupt them with big changes and new ideas. That said,
Hand it in, student. Just post it, Katya. Submit already, dude. And as for the former classmates or whoever you're sure are watching your every move, trust me: They're terrified you'll find their own fanfic LiveJournal or niche-market startup. It's most likely safe to get over yourself and chill out.


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University of Central Arkansas designated hitter Nate Ferrell hit a two-run single in the bottom of the eighth inning Sunday to propel the Bears to a 6-4 victory over the Missouri State Bears in the series finale at Bear Stadium.
Missouri State won the season-opening series, 3-1.
Ferrell's single to center field scored Justin Treece and Doug Votolato to break a 4-4 tie and give the Bears (1-2) their first win of the season. Votolato had reached on a throwing error by the MSU shortstop and Treece followed with a base hit to center. Scott Zimmerle walked to load the bases before MSU reliever Adam Anawalt got a strikeout for the second out of the inning.
Ferrell went 2 for 3 with two RBI and a run scored.
Junior transfer Ben Ancheff came on to pitch the ninth for the Bears and set the visiting Bears down in order for his first save. Junior transfer Chris Caudle got the victory with two innings of hitless and scoreless relief. UCA starter Connor Gilmore went six innings, allowing five hits and three earned runs but left with the game tied at 4-4.
Treece went 2 for 3 with two runs scored and is hitting .600 after the opening series. UCA pitchers held MSU to just five hits after allowing 13 and 15 in the previous two games.
UCA faces Wichita State at 3 p.m. Tuesday at Eck Stadium in Wichita.