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International Journal of Reconfigurable Computing
Volume 2012, Article ID 241439, 10 pages
The "Chimera": An Off-The-Shelf CPU/GPGPU/FPGA Hybrid Computing Platform
The Centre for Gravitational Physics, Department of Quantum Science, The Australian National University, Canberra, ACT 0200, Australia
Received 2 October 2011; Revised 4 January 2012; Accepted 4 January 2012
Academic Editor: Thomas Steinke
Copyright © 2012 Ra Inta et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The nature of modern astronomy means that a number of interesting problems exhibit a substantial computational bound and this situation is gradually worsening. Scientists, increasingly fighting for valuable resources on conventional high-performance computing (HPC) facilities—often with a limited customizable user environment—are increasingly looking to hardware acceleration solutions. We describe here a heterogeneous CPU/GPGPU/FPGA desktop computing system (the "Chimera"), built with commercial-off-the-shelf components. We show that this platform may be a viable alternative solution to many common computationally bound problems found in astronomy, however, not without significant challenges. The most significant bottleneck in pipelines involving real data is most likely to be the interconnect (in this case the PCI Express bus residing on the CPU motherboard). Finally, we speculate on the merits of our Chimera system on the entire landscape of parallel computing, through the analysis of representative problems from UC Berkeley's "Thirteen Dwarves."
1. Computationally Bound Problems in Astronomical Data Analysis
Many of the great discoveries in astronomy from the last two decades resulted directly from breakthroughs in the processing of data from observatories. For example, the revelation that the Universe is expanding relied directly upon a newly automated supernova detection pipeline [1], and similar cases apply to the homogeneity of the microwave background [2] and strong evidence for the existence of dark matter and dark energy [3]. Most of these discoveries had a significant computational bound and would not have been possible without a breakthrough in data analysis techniques and/or technology. One is led to wonder the astounding discoveries that could be made without such a computational bound.
Many observatories currently have "underanalyzed" datasets that await reduction but languish with a prohibitive computational bound. One solution to this issue is to make use of distributed computing, that is, the idle CPUs of networked participants, such as the SETI@HOME project [4]. It is clear that a number of common data analysis techniques are common across disciplines. For example, LIGO's Einstein@HOME distributed computing project, designed to search gravitational wave data for spinning neutron stars, recently discovered three very unusual binary pulsar systems in Arecibo radio telescope data [5].
These are far from the only "underanalyzed" datasets from existing observatories, and this situation is expected to only compound as we look forward to an ever increasing deluge of data. For example, the Square Kilometer Array is expected to produce about an exa-byte a day [6] (to put this into perspective, it is estimated that all the stored information created by humanity is roughly 300 EB [7]); just for fairly basic operation, this alone will require to be close to the projected computing power of the world's single most powerful computing system [8] at the expected 2020 date of "first light." There are a number of robotic survey telescopes either already, or scheduled soon to be, on-line to detect transient events, from near-Earth objects such as asteroids [9] to distant GRBs [10].
It should be obvious that many other sectors have exponentially growing appetites for computation, from military [11] through financial [12], even cinematic applications require the most powerful HPC systems [13]. Considering the common computational requirements of these systems, it is clear that a revolution in HPC technology is required in order to keep pace with projected needs.
2. Problems with Conventional Cluster-Based HPC Systems
Until very recently, the most powerful HPC systems (the "Top 500") were purely CPU based [8], although there is a very recent but significant shift towards the use of general-purpose graphical processor unit (GPU) coprocessing. However, many critics point out that the "Top 500" may not be representative of the true compute power of a cluster [14]. The negative corollary of the efficient compliance of CPUs with LINPACK is that the resulting rigid instruction set can compromise performance when performing operations not heavily dependent on dense linear algebra. As we show in Section 6 below, this is, only one feature of many that are vital to problems involving parallel computation.
Because power consumption, and hence heat generation, is proportional to clock speed, processors have begun to hit the so-called "speed wall" (e.g., Intel cancelled their 4 GHz processor line because of heat dissipation issues [15]). Furthermore, there is a growing awareness of the monetary cost of powering traditional HPC systems: over half the lifetime cost of a modern supercomputer is spent on electrical power [16]. Indeed, many computing clusters are sited near large generation plants in order to save on power transport costs [17].
It is also easy to forget that the concept of a "general purpose" microprocessor is a relatively recent idea—for example, only since the introduction of the 486 processor have Intel not used a dedicated floating point coprocessor. Meanwhile, hardware accelerators have occupied specialized niches, such as video processing and high-speed DSP applications. The most commonly available of these accelerators are the (general-purpose) graphical processor unit (GPU) and the FPGA. Easing or circumventing many of the issues with CPU-based HPC is becoming an attractive prospect to a growing cadre of consumers. Currently promising teraflop/s performance with a low initial capital outlay and without need of a specialized power supply or cooling facility, both the GPU and the FPGA are viable alternatives to purchasing many CPU-based units. Until recently, the development time associated with these platforms was considered rather high, especially for the FPGA. However, the programming interfaces for both have become more user-friendly. Finally, the future appears bright for both accelerator classes, as both have performance growth well exceeding Moore's Law, and consequently, that of CPUs [18].
3. Comparisons between CPUs and Hardware Accelerators
The long-standing workhorse of the vast majority of data analysts is the general-purpose CPU. Because it is expected to perform a range of different tasks, CPU processor designs cannot afford to specialize. Although the processor clock speeds are fairly high, it can take many cycles to perform an intensive computation, because it will be scanning for interrupts, and so forth. CPUs are generally very good at performing a multitude of separate tasks at a moderate speed and are efficient at moderating/coordinating a range of slave devices. The performance and merits of these devices should be fairly familiar to the reader.
Because GPU platforms were designed to efficiently perform linear operations on vectors and matrices, a general rule of thumb is that any operations that require intensive linear calculations are best made on a GPU. Many embarrassingly parallel computations rely on linear algebraic operations that are a perfect match for a GPU. This, in addition to the amount of high level support, such as C for CUDA, means they have become adopted as the hardware accelerator of choice by many data analysts. For example, a comparison of the GPU-based CUDA-FFT against the CPU-based FFTW3 on gravitational wave data analysis showed a 4X speedup for one million, and 8X for four million, points; this exact approach can also be used to detect radio transients with synthetic aperture array radio telescopes [19]. An excellent analysis of a range of algorithms heavily used in astronomy with applications including imaging, gravitational lensing, and pulsar characterization, implemented on GPUs, is given in [20].
FPGAs, on the other hand, of course, represent an entirely different approach to computing altogether. Because of their unrivalled computing flexibility, it can be difficult for the data analyst, used to a rigid instruction set-based processor, to be entirely comfortable with the low level required to construct an analysis pipeline. The majority of the applications in astronomy have been in instrumentation and data capture, such as the FPGA-based digital cross-correlator for synthetic aperture array radio telescopes [21, 22] or spectrometers [23]. However, there is a small but growing base of analysts willing to adopt an FPGA-based hardware acceleration solution, with applications including detection of gamma-ray pulsars [24]. There are a number of FPGA-based HPC facilities such as Janus [25] and Maxwell [26], and companies such as Starbridge, Inc. and Pico Computing, Inc. [11] offering FPGA computing solutions. A good survey of the state of FPGA-based HPC is given in [27].
Determining the relative strengths of each hardware acceleration class is highly algorithm (and data-type) dependent. There are many comparisons in the literature between FPGA, GPU and CPU, implementations of the same algorithms, ranging from random number generation [28] (where at 260 Gsample/s, FPGAs were found to be faster by a factor of 15 and 60 over a contemporaneous GPU and CPU resp.), video processing [29] (where FPGAs may have a significant advantage over GPUs when multiplying arrays of rank four or higher), convolution [30] (FPGAs are advantageous because of their pipelining and streaming abilities) to MapReduce [26, 31] (where the former show that GPUs considerably out-perform FPGAs and the latter show that an FPGA implementation of Quasi-Random Monte Carlo outperforms a CPU version by two orders of magnitude and beats a contemporaneous GPU by a factor of three), and least squares applications [32] (an FPGA implementation is slightly worse than that for a GPU, which is in turn slightly worse than a CPU, for large matrices). Some more general overviews are given in [33, 34]. However, one must be careful not to generalize performance without consideration of the detailed technical specifications of the components. Both FPGA and GPU platform designs are in a state of unprecedented flux, and hence relative performance benchmarks are likely to change also. This caveat notwithstanding there are a number of distinctions amongst each hardware platform intrinsic to the underlying design features.
With the above considerations in mind, we present here a system that attempts to exploit the innate advantages of all three hardware platforms, in order to attack problems with a computational bound that would benefit from a mixed hardware subsystem "heterogeneous" approach.
4. The "Chimera" Heterogeneous CPU/GPU/FPGA Computing Platform
We originally conceived a platform that would exploit the advantages of both FPGA and GPU accelerations via a high-speed backplane interconnect system [35]. A schematic is shown in Figure 1.
There are a number of platforms that implement a heterogeneous FPGA/GPU/CPU system. The "Quadro-Plex Cluster" [36] is a sophisticated sixteen node cluster with two 2.4 GHz AMD Opteron CPUs, four nVidia Quadro FX5600 GPUs, and one Nallatech H101-PCIX FPGA in each node, with a thread management design matching that of the GPUs. However, it does not yet appear to implement a combination of FPGAs and GPGPUs within an algorithmic pipeline, which is essential for our applications. Also, the FPGA architecture was designed to mirror that of the microprocessor, including full double precision support, which in general will not optimize the potential performance of the FPGA. The "Axel" [37] system is a configuration of sixteen nodes in a Nonuniform Node Uniform System (NNUS) cluster, each node comprising an AMD Phenom Quad-core CPU, an nVidia Tesla C1060, and a Xilinx Virtex-5 LX330 FPGA. From the perspective of Axel, our proposed platform would conform to the Uniform Node Nonuniform System (UNNS) configuration, or perhaps an optimized version of each node within an Axel-type cluster. There is a "desktop supercomputer" comprising a single CPU, GPU, and FPGA [38], used to model coupled resonator optical waveguides, although unfortunately the architecture and configuration of this system is unclear. Finally, there is a fledgling system that proposes to use a combination of GPUs and FPGAs for cryptoanalytic problems [39], although to date the applications have only been tested on GPUs.
We also would like the system to be scalable if possible, although the focus of this paper is the combined heterogeneity of the hardware accelerators in a single-node architecture. The main problems we are concerned with here feature embarrassingly parallel analysis pipelines, and so extrapolation to a cluster system ought to be relatively straight forward. The granularity of this system is dictated by the particular algorithm being used; the most coarse-grained pipelines will be those with a large reliance on GPU-based resources.
Finally, a significant constraint was an inexpensive initial outlay, which immediately restricted us to commercial-off-the-shelf (COTS) components. Table 1 lists the components of the heterogeneous system we describe here, which we call "Chimera," after the mythical Greek beast with a head of a goat, a snake, and a lion on the same body.
Aside from the actual CPU, FPGA, and GPU components, perhaps the most important element in this system is the high-speed backplane or interconnect. Because of COTS constraints, we eventually settled on the simplest solution, that is, that already residing as the northbridge system on the CPU motherboard. In this case, the interconnect protocol is Peripheral Component Interconnect express (PCIe) Gen 2.0, on an Intel DX58SO2 motherboard. Although the board has 2X PCIe 2.0 × 16 ports, only one 16 lane port is dedicated, the other is multiplexed with a third 8 lane slot. The maximum theoretical PCIe throughput, is therefore, 2 × 16 lane devices or 32 GB/s. These 32 PCIe lanes are routed to the I/O hub processor (the 82X58IOH, which we loosely term here a "northbridge") which implements Intel's Quick Peripheral Interconnect (QPI) protocol to the CPU. The QPI has a 25.6 GB/s point-to-point link to the CPU. In spite of the impressive performance of the motherboard we found, as expected, the PCIe bottleneck presented the most significant limitation to our computing model. We choose to ignore this limitation in what follows for several reasons.(1)The limitation is algorithm dependant, in some cases (e.g., generation of pseudorandom numbers) large-data sets are developed and processed solely on-chip. In other cases, processing pipelines may be organized to avoid this bottleneck.(2)FPGA devices, in particular, are provided with very high speed I/O connections allowing multiple FPGAs to process and reduce data-sets before passing them to the final, PCIe limited device.(3)The purpose of the Chimera is to prove the concept of the hybrid computing model using low-cost COTS devices. Having established that a hybrid design is limited only by interconnect speed the way is open for faster and more expensive interconnect solutions.
The Altera Stratix-IV FPGAs reside on DE-530 development boards, with an 8-lane PCIe interface, while the Tesla C2070 has a 16-lane PCIe interface. The development environment for the FPGAs was Verilog and ModelSim, while that for the GPUs was C/C++ for CUDA and nVidia's SDK libraries. Because there is not yet a widely available communication protocol that allows FPGA-GPU communication without the mediation of a CPU, we are currently developing kernel modules for the PCIe bus. A primary goal of the Chimera system is to provide access to high-performance computing hardware for novice users. This inherently means providing an operating system (OS) with familiar signal processing tools (e.g., MATLAB). Running the OS is naturally a task exclusively handled by the CPU, but it presents some difficulties because the security layers of the OS will usually deny direct access to the FPGA and GPU hardware. In the case of the GPU, this problem is solved by the vendor (nVidia) provided drivers, but, for the FPGA, an alternative approach is necessary: custom driver development is necessary. We opted for a Linux-based OS because we feel it is much simpler to develop drivers than for proprietary OSs. Like all modern OSs, GNU/Linux implements a virtual memory environment that prevents "user" code from directly accessing memory and memory-mapped peripherals. In order to directly control system hardware, such as a PCIe device, it is necessary to write code that runs in "kernel" mode. Linux permits these "kernel modules" to be loaded and unloaded into the running kernel via the insmod and rmmod commands. This provides a straightforward means to share data between the FPGA and GPU devices on the PCIe bus, as well as the system memory. A schematic of this stack design is given in Figure 2.
It is also possible to rebuild the Linux kernel, thus incorporating the module into a custom Linux kernel. The kernel code then provides a bridge between the user code space and the FPGA hardware. As these kernel modules are still under development, and the bottleneck from the PCIe transfer is simple to calculate for the simple examples below, we consider here the subsystem performance only. Hence, the run-time and data-transfer systems are currently fairly primitive. In order to optimize performance, the parallel programming models are algorithm dependent, including the number of threads and how data is shared. Data transfer between the subsystem components currently has only limited automation, and pipelines are mediated by the CPU, which is highly undesirable. However, we are in the process of building data transfer protocols (via the kernel modules) that depend upon the particular application but are implemented using a coherent level of abstraction.
Finally, this system was conceived with the explicit consideration of the significant trade-off between development time (especially associated with development of the FPGA related pipeline and PCIe modules) and performance. Hence, we consider only computing solutions that are likely to have a high reuse within the data analysis community.
5. Appropriate Algorithms for a Heterogeneous Computing System
As with most compute intensive problems, the implementation is extremely dependent on the underlying hardware and the most significant bottlenecks. Much consideration is required in the "technology mapping" from one system to another. For example, an important consideration for FPGA HPC applications is whether fixed or floating point calculations are required. Data analysts have become accustomed to assume that their pipeline requires single precision or more, without considering that this may actually decrease the absolute error of the calculation. It is also not entirely true that FPGAs perform poorly on floating point performance [40] (note that this is not necessarily the same as conforming exactly to the IEEE-754 single or double precision definition [41]; GPUs do not natively support denormals but now perform linear operations very well with most double precision calculations). Considering around 50% of FPGA logic can be consumed by tracking denormals, there are recent ingenious developments, optimizing floating point pipelines on FPGAs, such as Altera's "fused datapath" approach [42]. We consider here three important algorithms to attempt to illustrate the considerations required, and relative benefits of, mapping common problems to our heterogeneous computing system.
5.1. Monte Carlo Integration
The simplest illustration of the advantages of this system is the well-known Monte Carlo calculation of (the ratio of the circumference of a circle to its diameter) [43]. This proceeds as follows. A large set of points are created from pairs of random numbers, uniformly distributed between −1 and +1, such that they fall within a square of area 2 × 2 = 4 units2. Each point is then checked to see if it lies within a circle of unit radius (equivalently solving the inequality ). The ratio of the number of points satisfying this inequality to the total number of points then determines the ratio of the total area to the area of the circle. Yet the area of a circle of unit radius is , so the ratio will yield a numerical estimate of .
Because FPGAs have the unrivalled capacity to generate large quantities of uniformly distributed random numbers, and GPUs are vastly superior at taking squares (or square roots) over any other commonly available general purpose platform, it would be sensible if an FPGA were to generate the randomly placed points (in parallel), which were in turn directly given to a GPU to determine the placement of each point (i.e., within the circle or not). This calculation and how we anticipate performing it using a hybrid approach is depicted in Figure 3. We could implement a more sophisticated quasirandom version of this algorithm, that is, using a Halton, Sobol' or other low-discrepancy sequence [26, 43], but considering this a rather poor way to calculate , we restrict ourselves here to uniform pseudorandom distributions for illustrative purposes.
The pseudorandom calculation of was implemented entirely in the GPU and entirely in the FPGA. In both cases, two 32 bit unsigned integers ( pairs) were generated using a pseudorandom generator. These were squared and added and the result compared to unity. The limiting factor in the StratixIV530 FGPA was the available number of multiplier blocks which were necessary for the square operation. Our design required 5 DSP18 blocks per sampling module, allowing a total of ≈200 parallel units. Applying a conservative clock speed of 120 MHz, we achieved 24 giga-samples per second. Surprisingly, this is approximately an order of magnitude greater than our results for the GPU, which performed 100,000 trials in 47 sec, giving ≈2.13 giga-samples per second. These results agree broadly with those in [26], in that the FPGA calculation of the entire pipeline is about an order of magnitude faster than the GPU implementation, and many many times faster than that by a comparable CPU.
This result ought to be surprising, prima facie, considering that the multiplication intensive calculations involved in testing whether the points lie within the unit circle ought to favor the GPU. However, one must remember that a considerable amount of effort went into an implementation optimized for the FPGA, including the avoidance of the costly square root operation. We expect the GPU to perform a lot better, in relative terms, when the function to be integrated is more complicated than this extremely simple model. This argument, of course, ignores the fact that copying memory to devices takes far longer than these simple calculations (e.g., in the case of the GPU, about 42 times as long, at 2,118 sec).
5.2. Normalized Cross-Correlation
Template matching is one of the most important tasks in signal processing and is often achieved by computing the cross-correlation (or "sliding-dot product") between the template and a search signal. For example, cross-correlation is a crucial operation for resolving images in synthetic aperture array-based observatories such as the Very Long Baseline Array or the proposed Square Kilometre Array (SKA) [44].
The point in the search signal with maximum correlation is considered the best match to the template. For discrete one-dimensional signals, we seek to find , where . Essentially, we are treating the template, and a template-sized window of the search signal, as vectors in -dimensional space (where is the length of the template) and computing their dot-product. The Pythagorean relationship shows that, for vectors of equal length, this is simply a measure of the angular relationship between them, since .
Normalized cross-correlation (NCC) is so called because it divides the cross-correlation by the product of the magnitude of the vectors, thus calculating , regardless of the length of the vectors. NCC is widely applied in image processing, such as video compression, pattern recognition, and motion estimation where the signals are, of course, two-dimensional, real, and nonnegative. For image processing applications, the 2DNCC is given by (1):
Assuming the pixel data in question is always an integer and, since , we can equally express (1) as (2): provided we are only interested in finding the peak of the NCC surface.
Computationally, there are many options to accelerate (2) [45]. For most real-world datasets, calculation of the numerator is faster if the Fourier shift theorem is applied and the (unnormalized) cross-correlation computed via the usual transform multiply and inverse transform approach (although it is important to remember that in order to prevent wrap-around pollution it is necessary to zero-pad both images to be size() + size() – 1). The multiply-intensive nature of this approach, combined with the all-but-essential use of floating-point data types, leads us to conclude that the numerator will be best computed with the GPU.
The ideal platform to calculate the denominator, however, is not so easily assured. As the image data is integral and the only operators are the sum and square, which are both closed under the set of integers, this would seem an ideal candidate for an FPGA. However, because , it is also a task which might be well handled by a second GPU.
We evaluated the 2D NCC using a common image matching task. We exhaustively searched a 1024 × 768 pixel search image for an 8 × 8 template. In both cases, the pixels used were 16 bit unsigned greyscale integers. The numerator of (2) was calculated in the Fourier domain on the C2070 GPU and found to take 6.343 ms (≈158 frame/s). We then investigated two approaches to calculating the denominator: FPGA based, or using a second GPU. The FPGA implementation of the dot-product relied on the multiply-accumulate pipeline built into the DSP18 blocks in the StratixIV FPGA. Four DSP18s were required for each 8 × 8 dot-product block and, because very few of the FPGA's other resources were required, this was the limiting factor in determining the number of parallel units. For the StratixIV530 device, this allowed 256 dot-product modules to operate in parallel. As the DSP18 is a hard silicon block, the maximum clock speed was relatively high, at slightly over 400 MHz, giving a total value of roughly 10 giga-ops. For the search image size quoted, this would achieve ≈12.5 kframes/s. The GPU dot-product was profiled at one operation in about 1.4 nsec, or 715 Mop/s, corresponding to a frame rate of ≈894 frames/s.
Thus, in this implementation, ignoring the impact of the PCIe bottleneck, a hybrid system comprising a GPU working in tandem with an FPGA was found to achieve a better result than a system consisting of two GPUs. We would like to apply a similarly optimized algorithm to the correlation problem required by a synthetic aperture array observatory such as the VLBA or SKA [44].
5.3. Continuous Gravitational Wave Data Analysis
A much more complicated, and consequently useful, example is that related to the computationally bound problems found in gravitational wave data analysis. A number of mechanisms may cause rotating neutron stars to emit periodic distortions of space time (gravitational waves), which may be detected by ground-based gravitational wave observatories such as LIGO [46] or Virgo [47]. The data analysis pipeline is as follows: the data coming from the gravitational wave observatories is filtered, then template matching is applied. If no candidate is found, in order to determine the statistical upper limits, intensive Monte Carlo calculation of injections is required. This stage is so computationally intensive that it is often not fully implemented because of the prohibitive computational cost [48]. We estimate the Chimera platform will be able to provide these limits for approximately a dozen potential neutron star targets, including central objects in supernova remnants of unknown pulsation frequency. There are already GPU-based acceleration of similar pipelines used in gravitational wave data analysis; many FFTW3-based routines have been replaced with CUDA FFT, to enable low-latency detection of gravitational waves from coalescing neutron stars [19]. We see a similar pipeline as a natural application for the Chimera system we describe here, and we are in the process of implementing this.
5.4. Other Promising Algorithms
Many promising data analysis applications that are considered computationally expensive may be implemented rather simply using this type of heterogeneous hardware acceleration. For example, digital filter application is efficiently implemented on FPGA devices [49]. A number of promising analysis techniques based on compressed sensing [50] are considered computationally expensive. However, the most compute-intensive component, namely, the least-squares minimization routine, may be efficiently implemented on an FPGA via Cholesky decomposition [51–53].
6. Potential for Other Data Analysis Applications: Analysis via Berkeley's "Thirteen Dwarves"
Probably the most labor-intensive process involved in choosing the most appropriate platform weighting between the hardware accelerators in a heterogeneous system is that of identifying the most appropriate algorithms—especially their most efficient implementations—for a given pipeline and input/output constraints. Although we have identified a small number of algorithms here, it would be an interesting and valuable exercise to consider the possible classifications to determine which hardware acceleration combinations would be most appropriate.
In practice, there is a natural classification of problems merely by virtue of the similarity in computation and data movement through usage of the same software packages. Take, for example, FFTW/FFTW3 for spectral methods, or the dense linear algebra LAPACK/ScaLAPACK libraries. Indeed, the latter forms an important benchmark providing some measure of CPU performance (and possible entry into the popular "Top 500" list). However, we would like a more systematic approach to benchmark performance on parallel algorithms that are not necessarily strongly dependent on linear algebra.
In order to identify the likely future requirements of software and hardware design, Phil Colella identified seven parallel numerical methods important for science and engineering [54], known as "dwarves" (a reference to the Snow White fairy tale). This concept of a dwarf, as an "algorithmic method encapsulating a pattern of computation and/or communication," was further extended by the Department of Computer Science of UC Berkeley, to thirteen [55]. It is intended these "dwarves" comprise an algorithm classification system spanning the entire landscape of parallel computing for the foreseeable future ([55]; see Table 2). We see this approach as a promising means of determining the relative (dis)advantages of our Chimera system on other scientific problems. To our knowledge, this is the first attempt at the analysis of dwarf performance on systems heterogeneous at the hardware accelerator level.
The example of the Monte Carlo calculation of above falls under the "MapReduce" Dwarf: the Mapper function is each trial point, while the reducer just aggregates the counts. From the Chimera perspective, the mapper functions are either performed on the FPGA (the simple example above) or split between the FPGAs and the GPU, while the reducer runs on the CPU. The normalized cross-correlation would be classified within the "Dense Matrix" dwarf. The much more complicated case of the full gravitational wave analysis pipeline largely falls under the "Spectral Methods" jurisdiction, along with that of "MapReduce."
It is clear that many dwarves naturally map to each of the separate hardware accelerators. For example, the "Dense Matrix" dwarf equivalently relates to LAPACK/ScaLAPACK performance on a problem such as principal component analysis of a dense structure. Here, we should expect different performance for floating and fixed point operations, and hence we expect the GPU to excel alone on floating point (at least for matrices of up to rank 4 [29]), while the FPGA will be extremely competitive for fixed point versions. The same argument applies for naïve implementations of the "Sparse Matrix" dwarf, we expect GPUs to have superior performance calculating a sparse PCA problem in floating point, while the FPGA ought to well on fixed point. The "Spectral" dwarf generally comprises an FFT-based computation, such as wavelet decomposition. It is difficult for any platform to beat the GPU CUFFT library, and hence the GPU will be superior in most implementations, although for large numbers of FFT points, FPGAs may be more appropriate [40].
On the other hand, "Combinational Logic" problems (dwarf 8) such as hashing, DES encryption, or simulated annealing, are extremely well suited for the logic-intensive FPGA. It is also clear the "Finite State Machine" dwarf (13), such as control systems, compression (e.g., the bzip2 function), or cellular automata, can be most easily optimized by an FPGA. For example, consider a simple implementation of a 4-bit TTL (Transistor-Transistor Logic) counter, requiring 4 XOR gates, 3 AND gates, and 4 1-bit registers, our Stratix-4 could produce ≈120 k operations per clock cycle, or roughly 36 peta-op/s.
What are not so clear are problems requiring conditional elements or communication between hardware accelerators that would require prohibitively costly transfers across the back plane. The "N-Body" dwarf generally consists of calculations such as particle-particle interactions. A Barnes-Hut-based particle-particle N-Body model, as used for modelling astrophysical gravitating systems [56], would be able to calculate the changes in interaction on a GPU, while the memory-intensive cell (spatial position) data would be optimally handled by an FPGA. Although there is an implementation of an Ising "spin-flip" model on the Janus FPGA cluster [25], an example of a "Structured Grid" dwarf, a simple Ising model with a limited number of FPGAs would be better optimized using a GPU in addition.
The "Unstructured Grid" dwarf involves Adaptive Mesh Refinement, where calculations may be simplified by considering that only salient points in a space need be calculated, such as for adaptive finite element modelling (FEM) or computational fluid dynamics (CFD). The CPU will be useful in this case to tally changes in the mesh and co-ordinate calculations on salient mesh points using the FPGA and/or GPU.
Because of its conditional nature, "graph traversal" (including selection (Section 3.4, [43]), searching (Section 8.5, [43]) or decision trees) requires coordination from a CPU, and hardware acceleration is dependent on the particular application. "Dynamic Programming," such as the famous "Tower of Hanoi" problem, also requires CPU coordination, and also memory-intensive routines that are likely to benefit from an FPGA.
"Backtrack/Branch-and-Bound" problems, including search and global optimization problems, also depend on coordination from a CPU and again are generally memory intensive. "Graphical Models," such as Hidden Markov, probabilistic, neural, and Bayesian networks are also heavily dependent on coordination.
In light of these arguments, we summarize the most promising subsystem combination to apply for each dwarf as a Venn diagram in Figure 4. Of course, this should be understood that the performance is heavily dependent on the particular implementation, generation of subsystem (including on-board memory, number of LUTs, etc.), and interconnect speed.
To characterize the performance of the Chimera system, we would like to analyze representative problems in each dwarf in the future using appropriate benchmark packages such as, for example, the "DwarfBench" package [57] or "Rodinia" [58]. Such a benchmark would be of use to researchers considering the benefits of this approach for their own work.
7. Discussion
We see a heterogeneous CPU/GPU/FPGA solution as a viable future platform for ameliorating some of the computationally bound problems in astronomy based on performance, initial outlay, and power consumption considerations. Because of the outstanding progress made in microprocessor technologies, most members of the astronomical and broader scientific community will not have considered the possibility of including an FPGA-based accelerator to their analysis pipelines; indeed the adoption of the GPU is relatively new within the data analysis community.
However, this solution is not without challenges. There is a significant investment required in development time. This begins with the "technology mapping" stage, which can require many hours for a modest pipeline, such as in Sections 5.1 and 5.2, each of which required considerable thought of how to distribute compute resources, including small-scale trials using MATLAB as a development environment, comprising one to two hours each. The GPU programming for these two examples took a total of about five hours, largely thanks to nVidia's comprehensive CUDA SDK support. However, because the degree of optimization of the FPGA pipelines meant the total amount of time spent "programming" was approximately forty to fifty hours, the majority of which was spent in the synthesis/debugging phase using ModelSim. Although we have not yet implemented the example in Section 5.3—which requires the dynamic range given by floating point types—considerable development time was saved using Altera's DSP Builder, which interfaces easily with Mathworks' Simulink. Another issue to be aware of is that a high degree of hardware optimization generally means a trade-off in problem-size scalability. For example, in Section 5.1 example, the pairs of numbers are each 32-bit and the cases under-/over-flow are well known; a naïve scaling to, say, single precision floating point pairs would quickly reduce the number of parallel units on the FPGA. In example Section 5.2, if instead of an 8 × 8 template, we were to use 32 × 32 template, performance would scale very poorly because the limiting factor in performance is the number of DSP18 blocks on the StratixIV530 FPGA.
A promising advantage of this platform is the low power consumption. Taking the peak rated single precision performance of each subsystem gives 1.02 Tflop/s for the Tesla C2070, drawing a power of 228 W. This gives 4.3 Gflop/s/W, or 4.3 Gflop/J. Compare to the StratixIV, with 500 Mflop performance, drawing around 20 W at this performance, yielding roughly 25 Mflop/s/W. Perhaps more importantly, the FPGA draws virtually no power when not performing intensive calculations, unlike both the GPU and CPU systems.
Although we have shown the merits and challenges of a mixed system, the advantages are obvious for a diverse range of parallel computing tasks, as shown by analysis of Berkeley's "Thirteen Dwarves." This paper hopefully provides a blueprint for future researchers intending to perform computationally intensive investigations and are willing to embrace a heterogeneous computing platform.
The authors wish to thank the Australian National University and Altera Corporation for their generous support. R. Inta is supported by an Australian Research Council "Discovery" project and D. J. Bowman is supported by an Australian Research Council "Super Science" Project. They would like also to thank Martin Langhammer for helpful discussion, and the anonymous reviewers, whose suggestions greatly improved the manuscript.
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Tuesday, March 30, 2010
•< toy box arts >•
Amazingly believable vintage-style toys, made by artist Aneri Kärkkäinen, are for sale at Toy Box Arts' Etsy shop. Also, check out Aneri's website to view her paintings.
Posted by Jeanie Nelson at 4:43 PM No comments:
Monday, March 29, 2010
:: Carter's New Store ::
Check out Carter's brand new online store. Not only are all the products heavily discounted from the MSRP (the price you'd find if you bought it at a department store), but you can get 20% off your first order of $50 or more: enter promo code CCC20. And get free shipping on orders over $50. Yay!
Posted by Jeanie Nelson at 10:38 AM 1 comment:
Labels: childrens fashion
Saturday, March 27, 2010
{ The Paper Nut Easter Cards }
Need fabulous Easter cards in a hurry? You can order these for less than the cost of a regular greeting card, then print out as many as you like from the comfort of your own home! PDf will be emailed to you within 24 hours. Check it out here at The Paper Nut Etsy shop.
Posted by Jeanie Nelson at 2:32 PM 1 comment:
Labels: DIY, Easter, etsy, the paper nut
Friday, March 26, 2010
~ land of nod ~
Land of Nod has some new adorable dresses.dresses. And some really cute boy clothes (sorry I always neglect the boys!) Also, check out the awesome things I found in the sale section (most of these items are lower than half price):
"you're a natural" dollhouse $99
under the big top storage tent $79
puppets $4.95 each
jumbo memory game $14.95
Posted by Jeanie Nelson at 8:51 AM 1 comment:
Labels: childrens fashion, Land of Nod, Toys
Wednesday, March 24, 2010
<< kinchi >>
Retro fabrics put together in truly unique, handmade pieces by a Dutch designer. Etsy shop here, and website here.
Posted by Jeanie Nelson at 3:09 PM 1 comment:
Labels: childrens fashion, etsy
Tuesday, March 23, 2010
= Brio =
Check out the amazing toys available from Brio. The Swedish-originated company is over 120 years old. These toys are extremely high-quality, safe, educational, and known for being past down from generation to generation. Plus they'll make your abode more stylish even if the floor is cluttered with toys. The adorable little horse on the main page, which comes with the horse track set, is called "Darling Horse" is one of the several "My First Brio" toys. The cat, dog, Squid, and penguin are for sale on Amazon. The Darling Horse I found on Sale at Whistle Stop Hobbie & Toy.
Posted by Jeanie Nelson at 8:24 AM No comments:
Labels: Toys
Monday, March 22, 2010
•o• rubber ducky •o•
Cute "Odd Ducks" by Boon (available at Target). Not only are they covered in nifty mod patterns, but they are each a different, uh, "girth," if you will. Cuteness.
Posted by Jeanie Nelson at 8:22 AM No comments:
Thursday, March 18, 2010
<<< liberty of london fabrics >>>
A sort of continuation of yesterday's post, I wanted to share all these sweet fabrics made by Liberty of London. Taken individually, each seems pretty simple, but what I am so impressed by is the overall vision of how these prints work together to create this eclectic bohemian wildflower feel. So nice and girly.
Posted by Jeanie Nelson at 9:09 AM 5 comments:
Labels: fabric, liberty of london, patterns
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subset: commoncrawl


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The Bereavement Counselling Service at St Benedict's Hospice provides one to one counselling to families experiencing bereavement. We are able to offer counselling to the carers and family members of patients receiving support from St Benedict's who are facing the loss of a loved one and through the bereavement process. We can also offer counselling to patients coming to terms with their diagnosis and with their own feelings of loss.
Coping with the loss of a loved one can feel overwhelming. Often it is difficult to talk to those close to you about your fears and anxieties, concerns about the future and the difficult emotions you are experiencing. Talking to a counsellor offers you a confidential, safe place to be listened to, understood and accepted, to help you to make sense of how you feel at this difficult time.
The service is provided by fully trained and qualified counsellors.
Bereavement is a unique experience for each individual and those who attend may be at different stages of their grief. It can be helpful to talk to others who may be experiencing similar feelings to yourself and share experiences. The group provides an opportunity for mutual support and understanding and is facilitated by a Bereavement Counsellor. The group is open to any bereaved friend or relative of a patient who was supported by St Benedict's Hospice or Specialist Palliative Care Services.
We offer a range of services which provide support for patients 24 hours a day.
We offer a range of education and training opportunities to NHS and non-NHS staff.
Find out how we fundraise and how you can help.
St Benedict's Hospice has provided specialist palliative care to the people of Sunderland and surrounding districts since 1984.
St. Benedict's Hospice and Centre for Specialist Palliative Care
St. Benedict's Way
Sunderland, SR2 0NY
Tel: (0191) 5128400
Registered Charity No 1019410


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Regardless of how much you know or don't know about the current state of politics in our country, it's easy to feel overwhelmed and powerless during these weeks leading up to the coming presidential election. Fierce debates, the official presidential ones and the ones that play out on social media fought by strangers behind screens, have helped create an uncomfortable tension that can be felt by everyone here in America and abroad. Sometimes it makes me afraid to ask questions. Other times it makes me want to retreat to somewhere where politics don't matter.
But politics do matter. This election matters because it affects me, my friends, my family, and people I've never even met.
Politics matter because people matter.
Here are some questions to answer to make sure you're ready to use your vote as your voice and #Act4MentalHealth (http://act4mentalhealth.tumblr.com/):
Are you registered to vote? Do you know where your polling place is? Do you have a time and date scheduled in your personal calendar to vote? Remember, you can vote early if you know the dates and times of the polling location of your choice. Otherwise, polls are open from 7am-8pm on Tuesday, November 8th, General Election Day, in Wisconsin. (If you have a disability and are experiencing any accessibility problems on Election Day, call the Wisconsin Disability Vote Coalition's toll free hotline: 1-800-928-8778) Do you know who you are voting for? Do they support who and what you care about? (Go to: https://myvote.wi.gov for more how-to voting information)
I care about a lot. It's sometimes difficult to prioritize what needs attention when there is so much healing to do in this broken mental health care system, but being a part of a community that understands and cares about the things that I do makes it simpler. NAMI has put together a list of our national community's top concerns when it comes to mental illness. Check it out below:
NAMI's 2016 Legislative Priorities
Increase the availability of quality mental health care
Promote early identification and intervention
Reduce criminalization
Enforce mental health insurance parity
Support mental health caregivers
Do our candidates care about these priorities? Do they have a well thought-out platform that addresses mental health and supports people with mental illnesses in the U.S.? Have they spoken about mental health publicly, and, if so, how do say they plan to support people with lived experiences? If you don't know, that's okay! All it takes is a Google search to find the answers. (Just make sure you get your information from credible sources and not opinion pieces.)
It is our responsibility to do what we can to affect politics because, at a very basic level, it is right to care about people. It is right to ensure that those in elected offices care about people, as well. Please understand that you matter even when you feel powerless. Your vote has power, and, I promise you, your vote matters. Do the right thing.
Written by Leah Rolando, MSW Intern, NAMI Wisconsin


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A Separate Heaven
by Alex Disanti
ROOM WITH BOOKS encourages our readers to follow the tour and leave comments!
GENRE: Fiction/Romance
Step into a world of riveting drama. Enter A Separate Heaven, a story comprised of power, wealth, and romance, multifaceted characters, and complex relationships. A novel by Alex Disanti. From Long Island to the shores of the Mediterranean, this exciting series spanning twenty five years in the lives of the Gianelli and Hamilton families will hold you spellbound.
from Book Two
They had been back on Long Island only a week when the earth quaked, shattering their peaceful existence. It began slowly, a tiny crack on the surface, but before it was over, it opened into a chasm of such upheaval, such misery and strife; it threatened to swallow them and rob them of everything.
It started innocently enough, on a Sunday morning as Dominic showered while Paige cooked breakfast. After pouring herself a second cup of coffee, she opened the Times. There, staring up at her from the front page were the faces of the two men, the ones who had confronted her in Salerno. She recognized them immediately.
In bold letters, the headlines proclaimed: "Bodies Identified as Missing Federal Agents." It was like being slammed in the chest with a bat. Paige could hardly breathe and she began to shake violently.
* * * *
This was how Dominic found her. "Paige! What is it? What's wrong?"
She gasped, "Them!"
"Who, Paige? Where?"
She pointed toward the paper on the counter. "Them!"
As he rummaged through a drawer, searching for an inhaler, he glanced at the pictures and read the headlines, but he didn't understand. "What about them?"
He located an inhaler and held it to her mouth. "Breathe! Come on, Paige, a deep breath in! Now! Again!"
He took her to the den and sat her on the sofa, wrapped a throw around her. He knelt in front of her. "Paige, please, tell me what's wrong!"
"Salerno. L'Allegreto. It's them."
"The ones in the paper?" She had to be mistaken, he thought. Why would U.S. agents have accosted his wife, threatened her?
"Yes, it's them, Dom. It is!!"
"But Paige, those men were federal agents." His mind was racing.
"I don't care. It was them!" She was crying now. "And they were liars! They were horrible, evil men and I'm glad they're dead!"
It is my pleasure to welcome Alex Disanti, author of A Separate Heaven, to Room with Books!
Thank you so much for having me and for hosting A Separate Heaven. It is my pleasure to be here!
Please tell us about yourself, Alex.
I'm a lifelong Texan. Favorite things include writing (of course!), stargazing, music by Zack Brown, Willie, and the Avett Brothers, novels with a lot of page-turning drama, hanging out with friends and family.
Did you always want to be a writer?
I don't think I ever "aspired" to be an author in the sense that from childhood on I thought "Oh, I want to be a writer!" But I always loved words. I learned to read at the age of four – from a newspaper, the Dallas Morning News to be exact. My father wasn't fond of children's books. He showed me how to look up words in the dictionary. From that point on I was an avid reader and always on a quest for the meaning of a new word.
How long have you been writing and who or what inspired you to write?
I began writing poems and short stories at the age of nine. A pen, paper and my imagination provided my favorite pastime. Until the series I wrote short stories that would play well on the Hallmark network. A Separate Heaven took another direction. The short stories I wrote involved little or no research. Certain aspects of A Separate Heaven involved a lot of research. For instance, I have never been to Italy and the Amalfi Coast is a principal location in the books.
If I may take an extra minute or two here, I would like to share the story of how I found the artist who provides the covers for my books. It still inspires and motivates me because it is a perfect example of "meant to be" even if you don't normally believe in signs.
I had told my daughter that for the cover of the first book I wanted a picture of a sunrise or sunset over water. She found two photos by David Humphries. His name was all I knew. It took a while but I did locate him. There are a lot of David Humphries in the world. My David turned out to be an artist who lives in Yorkshire, England. Several weeks after contacting him and gaining permission to use his photos I received a message from him. He told me the photos were taken off the coast of Italy when he and his wife were guests on a friend's yacht. If that wasn't enough of a coincidence, a week later I received word that his wife had located pictures of that particular vacation and the name of the boat was Heavenly Daze.
When life interferes with my plans and the road gets bumpy, this story reminds me to smile and enjoy every mile of this journey. What are the odds that I would find an artist thousands of miles away and the story would unfold as it did? Thank you for allowing me to share it with you.
Do you have a job in addition to writing and would you tell us more about it?
Currently, writing is my full-time occupation, but I have worked as a histologist doing tissues and slides for pathologists, and in quality assurance writing procedures and specifications for an engineering and construction firm that built gas plants and specialized in cryogenic processes. I was also a welding inspector.
How would you summarize this book in less than 20 words?
A Separate Heaven…where love is found, lives are changed, loyalties are tested, and forgiveness isn't always an option.
Now, let's talk about writing and how you came to be a published author.
When did you first consider yourself a "writer"?
After I began writing A Separate Heaven.
How long did it take to get your first book published?
Seven years.
What can we expect from you in the future? More of the same genre? Books of a different genre?
Well, A Separate Heaven, which initially I thought would be one book has become a series of seven books. I am currently working on book five.
My ultimate goal for A Separate Heaven (beyond being a best seller of course!) is a television series.. I have a collection of short stories I want to publish. It will be titled Seasons of the Soul. Beyond that I have plans for two novels…one about a Texas family, the other about a middle aged blue collar worker who makes some midlife changes when his wife leaves him.
Who is your favorite character from your books and why are they your favorite?
Dominic Gianelli is my favorite character in the series. His inner strength, his power and his ability to make his own justice appeal to me. And that he is sexy without being a "pretty boy".
What is your routine for writing?
I don't know that I have a routine. I carry chapters in my head and when I have the details worked out, I write. I never outline. I write (mentally) while doing other things. I admit to some OCD. I like order. My favorite times to create are when I am driving or walking.
Do you choose a title first, or write the book then choose the title?
Title comes last for me. For A Separate Heaven, I didn't change titles or use a subtitle even though there are seven books. A Separate Heaven simply best describes the life of Dominic and Paige, the main characters. There is a scene in book one where Dominic uses the term.
Are there any hidden messages or morals contained in your books?
I do play on the fact that good people sometimes do bad things for good reasons. That sometimes people whose lives appear idyllic are anything but that. Also that there are those with authority over others who should hold themselves and be held to a higher standard, but instead make it a practice to manipulate and abuse.
Which format of book do you prefer, eBook, hardback, or paperback?
Paperback, hardback, and then eBook.
What is your favorite book and why is it your favorite? How many times would you estimate you've read it?
I have at least 100 favorites but, to narrow it down… I have read Out of Africa at least ten times. I would love to have known Karen Blixen. I find her quite brave and fearless.
The Godfather, The Horse Whisperer, To Kill a Mockingbird and Davita's Harp I have read an equal number of times. I am a "mob groupie" so The Godfather is perfect escapism to me.
Do you read all the reviews of your books?
That's enough of the serious business. How about a handful of fun questions?
What is your favorite food? Steak, medium rare.
Who is your favorite singer or group? The Avett Brothers.
What is your favorite color? Black.
What is your ideal getaway dream vacation? Italy.
What final words would you offer to our readers?
First of all, a big thank you for being here at Room with Books with me and for allowing me to tell you a little about myself and my series, A Separate Heaven.
Too, I would like to say that whether it is success in writing or something else that is your goal, perseverance and a passionate belief in yourself will be your best friends. I believe there is no substitute for dogged determination. May your star shine brightly! Thank you again!
Thank you for spending time here at Room with Books. I appreciate your time and wish you the best with your series. I hope you will come back again!
Alex Disanti lives in the Texas Hill Country. While writing has been a lifelong love for her, A Separate Heaven is her first novel. Early works were mainly poetry and short stories. As A Separate Heaven progressed from thought to paper, friends and family began reading the manuscript. Then, in an effort to test the marketability of the material, she enlisted the aid of what she calls her "test readers." These readers vary in age, occupation and background. It simply grew from there. Alex's rich detail brought the characters to life, and the ensuing chapters could not come quickly enough for her readers.
Facebook ~~ Facebook Page for A Separate Heaven
Twitter ~~ Website/Blog
Book 1 ~~ Book 2 ~~ Book 3
Alex Disanti will be awarding a $25 Amazon/B&N gift card to a randomly drawn winner via Rafflecopter during the tour.


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Mostly about dogs, but books as well. And sometimes I have other stuff on my mind. And now: a blog about my ovarian cancer.
Friday, 10 December 2010
On the move
On Tuesday Margot got to move to the hospital in Vaison which is the nearest thing to a hospice that I have seen. She had a very nice room with a view over the old town and a good level of doctors, nursing staff and helpers. Unfortunately the move, the change in conditions, or something made her very agitated and for two days she was not at all calm. Even though I was with her most of the time all she wanted to do was leave and come home. She is much more tranquil today but still wants to be at home. We have been talking with the hospital-at-home people and local nurses and if she remains stable we might be able to have her at home again next week with the option of returning to the hospice if it does not work out.
Again, thank you all for your messages which I try and pass on but Margot is not always tracking 100 percent. Nick
8 comments:
Praying for you both.ReplyDelete
My thoughts and prayers are with you both.ReplyDelete
- Anonymous10 December 2010 at 23:34:00 CET
Our thoughts and prayers are with you both. We hope Things will even out and Margot will be able to be comfortable.ReplyDelete
Kathy and Courtney Hays
I pray she gets home. It makes a world of difference. I can't believe she hasn't tried to go on her own, my fierce friend.:) You'd be better able to deal with everything, too.ReplyDelete
I sincerely wish you the best here, Nick. It's a very tough stage to go through. Give Margot hugs and kisses from me and Caitlin - don't need words to understand those. Love, US xoxoxoxoxo
- Cheryl (who usually posts as valrico canine)11 December 2010 at 03:32:00 CET
Glad they were able to move Margot closer to home. Maybe she can get home, if you can get the care to come to you. The candles are still lit for both of you - and beaucoup hugs and kisses from both of us and big slurpy licks from Rambo!ReplyDelete
- Jo Tyson11 December 2010 at 23:14:00 CET
Dear Nick, thanks for keeping us updated, when I'm sure it's the last thing on your mind. I do hope that Margot can find some peace soon. My thoughts are with you both.ReplyDelete
Much love
Thanks for the news, Nick. Thinking of you both.ReplyDelete
- Anonymous14 December 2010 at 16:15:00 CET
I hope she can make it home, Nick. Thank you for the update.ReplyDelete
You are both in my thoughts.


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Monday, April 27
In love with lilacs
They are all gone now, but I enjoyed our lilacs this year so much. I just wanted to share them one more time!
We had a bountiful bloom this year. Probably from having several ice storms during the winter. I know lilacs like a hard freeze during winter to bloom well.
There's nothing quite like the beautiful scent of lilacs!
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The MiniMc and MiniMc SFP switching fiber converters are the smallest, most reliable and most cost-effective switching 10/100 Mbps media converters in the industry.
Media conversion is the most cost-effective solution for extending the productive life of legacy wiring plants and equipment while allowing implementation of new technologies. Media conversion's greatest benefits are flexibility and cost savings.
Measuring less than 3.5 inches deep and 2 inches wide, the MiniMc is the industry's smallest media converter with both data connections on the same side of the unit, and at a fraction of the cost of other alternatives. Plug-and-play operation with a variety of model types and powering options make the MiniMc series easy and convenient to use.
The MiniMc SFP requires one MSA compliant fiber optic SFP module (sold separately) to operate. Copper SFPs are not supported. B&B Electronics offers a full range of compatible SFPs.


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If you think vans are boring, you're wrong. Here's why.
If you think vans are for boring people to drive their kids to and from after school practice with, then you'd be sadly mistaken. Vans are absolutely capable to combining fun and utility, and they're quirky enough for you to stand well apart from your friends if you own one. Here are some of the best vans out there, according to you.
No, the Espace F1 wasn't actually a production van—but it needs to be featured. It used the V10 drivetrain from the 1993 Williams FW15C F1, grafted into the body of a normal Renault Espace van. It could get from 0-60 in under three seconds
The name "S-Cargo" is a play on words, standing for "Small Cargo" and for sounding like the French word "escargot," meaning snail, which references the car's shape. Is it the ultimate weird budget delivery vehicle? We think so.
There is perhaps no crazier van than this 1000-horsepower Odyssey built by tuner genius Bisi Ezerioha. It retains the standard Odyssey's front-wheel drive layout, powered by a fully built version of the car's 3.5-liter V6 a massive turbocharger. It can do some serious burnouts.
You can't buy VW's newest habitable van in the US, but we still think it's worth a mentioning. The California XXL comes with things like sleeping quarters, a bathroom, and even a kitchen. Perfect for spectating any race weekend.
The fourth-generation Ford Econoline could be optioned with a V10 engine. It wasn't a great V10, but does that matter? V10! You could pair that V10 with bench seats, carpet, and a headliner to make transporting all of your friends and family into an event. Hell, you could even live out of them for a while, if you were motivated enough.
The Toyota Van had a much more badass name in Europe: the Space Cruise. How can you own something like that and not feel cool? Sure, it was super odd-looking, with rear-drive and an engine stuck under the driver's seat like an afterthought. But the crown jewel was the that was cooled by air-conditioning refrigerant lines and came with spill-proof ice trays.
If you're wondering why every van on the market in the US now seems taller than they ever did, you have the Sprinter to thank. Because they're longer and taller than the usual US full-size vans, which means you can maximize both your cargo space and your road-going influence. Plus, if you get the newest Sprinter, it comes with lane keeping assists, forward collision alerts, and blind spot detection—which means it's basically an S-Class that can haul drywall.
The first generation Toyota Previa lineup included a . And the engine didn't just sit in the front like in most vans. No, it was mid-mounted and you could get it with all-wheel-drive. Then you could tell everybody that your car was basically a Lamborghini and watch their their faces when you pull up.
You could classify the Mazda5 as a and you wouldn't be wrong. You can fit six people in it, and because it's smaller than most vans, you're a lot more agile and maneuverable when you're driving through traffic or the city. You used to be able to get it with a six-speed manual gearbox, but Mazda dropped that for the 2015 model.
From the outside, the R-Class was nothing special at all. But underneath the hood of the R63 AMG you'd find a 6.2-liter V8 that made some serious power: 503-hp and 465 lb-ft of torque. And because that power went to all four wheels, you'd give a comparable 911 something to worry about if you were in the mood. With a trunkful of groceries.
The "MPV" moniker stood for "Multipurpose Vehicle," which was Mazda's first take on a minivan. And moving away from a traditional minivan also meant that it didn't have the sliding rear doors like everyone was used to. You could also get it in all-wheel-drive with a manual gearbox. It was basically a rally van.
If there was a car that could make anyone smile, it was the Volkswagen Microbus. These days, you see them painted and customized and limited only to their owners' imaginations. And with rumors surrounding the possibility of VW bringing an all-new and all-electric microbus, we could be seeing a revitalization of sorts.


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fairytale beginning
No two Fredericksburg weddings are alike! Our variety of venues and access to amazing local talent will make it easy to create a celebration sure to be remembered by you and your guests—for years to come.
Whether you invite 20 people outside under a 100-year-old oak tree, or 500 to a grand indoor celebration, you can have the "magazine feature story" look you've always dreamed of. Silver candelabras or hand-cut wooden votives. It's your style. With that touch of Texas Hill Country class.
Historic 150-year-old churches. An abundance of quiet and cozy B&Bs. Picturesque wineries and vineyards. Breathtaking Texas Hill Country scenery. A contagious laid-back and relaxed pace. Some would say "love is in the air." We couldn't agree more.


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India woke up to a historic news today. Its low-cost Mars Mission Mangalyaan entered the Mars Orbit after travelling a distance of 666 million km (414 miles) for more than 10 months. Indian Space Research Organization proudly announced Mangalyaan's entry into the red planet's orbit this morning at 8 a.m India time.
India has achieved what only a few countries in the world have been able to achieve – the US, Russia, and a European space agency. The tremendous breakthrough for ISRO came at a cost of just $75 million compared to Nasa's spacecraft Maven which cost a whooping $671 million. While India managed to pull it successfully in the first attempt, many countries have failed in their Mars mission including China in the year 2011.
Prime Minister Narendra Modi was quick to make a statement on the achievement by Indian Research Space Organization (ISRO). He said, "History has been made today," and that "We have dared to reach out into the unknown and have achieved the near impossible."
The spacecraft Mangalyaan will study the red planet atmosphere and scan for methane presence in it. Though it won't land on Mars, it is likely to give out valuable information in the days to come.
The news of Indian mission entering into Mars orbit has come at a time when PM Modi is set for his US visit. He now has a lot more to talk about in his address to the United Nations.


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Jonathan Vogel-Borne
When Debbie suggested that we might co-lead a 2013 FGC workshop on practicing prophetic ministry, I was immediately clear to say yes. The prophetic element of ministry is one aspect of the many faceted ways that the Holy Spirit calls and empowers us to fulfill God's purposes. I hear this call and this power rising up among us, rising up to meet the ever growing challenges on our planet. I pray that our time together will help each of us see where our gifts of prophetic ministry can best be used to fulfill God's promise of healing and unconditional love.
Now this coming summer, 2014, Debbie & I are again planning to co-lead a similar workshop, but this time from the perspective of "prophetic listening." All prophetic action begins with deep listening to God's Spirit, helping us tune in to the underlying patterns that connect us together and bring all of creation into wholeness.
A little more about me—I was born into a Quaker family in Pasadena, California where we attended Orange Grove Meeting, part of Pacific Yearly Meeting. For most of my adult life, I have followed a call to ministry, seeking God's constant loving presence, prompting us to deeper unity, a oneness with each other and with creation. That ministry has been of service providing administrative and fiscal backbone to such Quaker institutions as, Young Friends of North America, the 1985 World Gathering of Young Friends, Cambridge (MA) Monthly Meeting (where my membership currently resides), New England Yearly Meeting, Friends United Meeting, Friends World Committee for Consultation, and Friends General Conference. At times I have described my ministry as providing the framework for other's ministry to flourish.
I live in Cambridge, MA with my spouse, Minga Claggett-Borne, and have two grown children, Elias (21) and Asa (26). In addition to Quaker ministry, I love to play music (violin, guitar, bass) and I am a graphic artist, working in print media and website development.
Jonathan Vogel-Borne, October 2013
Cambridge, MA


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Browse cities
Try single words like "clothes" or "furniture". Too many words will not return any results.
Showing 1 of 1 sales. Zoom out to view more.
406 3rd Ave, Woodruff, WI 54568
Household full of items, furniture, refrigerator, decorations, etc. Plus garage and shed boats, lawn equipment, tools.
Sale dates: Wednesday, May 22, 2019 - Tuesday, May 28, 2019Post date: Tuesday, May 21, 2019
▻ Details ♥
Find more great estate sales around Boulder Junction on EstateSales.org.
View all cities in Wisconsin.


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Ugly Duck or Common Eider?
Through a long process of elimination, I have finally decided that this is a juvenile and/or female Common Eider (a life-lister for me!). He was in the bay every day of the two weeks we were on Tahanto, and quickly became a familiar sight. Unfortunately, the name I first uttered at the sight of him stuck, and we all called him Ugly Duck.
Even with limited internet access, you'd think such a distinctive face would be easy to identify. Nope. The coloring was a little off from the field guides, his size seemed far too small, and some of the behavior displayed by Ugly Duck remains puzzling still.
A Common Eider is a diving duck. Our duck put his head under water all the time, but he that can't really be described as diving. He was rarely completely submerged. He'd stay under for a second or two at most.
These enormous feet, which I didn't notice until he climbed onto this rock, were an additional and very helpful clue. The flap on the back of the webbed feet is characteristic of a Common Eider.
This is not Ugly Duck, but is clearly the same species. This looks much more like a Common Eider, and even the pose is typical for Common Eiders. Eventually, we were all convinced that Ugly Duck was also a Common Eider. It is quite likely, however, that he is actually a she!
2 comments:
- AnonymousSeptember 14, 2010 at 1:36 AM
You're right! This looks like a sub-adult male common eider. The white under-wings are uncharacteristic of female common eiders.ReplyDelete
For comparison, check this out:
It's great when we can puzzle out an ID of a new bird without help. But if the youngster was just playing at diving, I guess we should worry about it. He/she also has to do it without or not make it. Nature does not have much use for the inept. Is that what sets us apart, perhaps?ReplyDelete
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Wednesday, May 11, 2011
Long Weekend
Originally I planned to go too, with the kids. Then I changed my mind, thinking it would be too much work.
Then this week I realized that next Thursday morning, Steve will leave and be gone for 5 days.
That's 5 days as a single mom with a 2.5 year old and an 11 month old...
Naturally I went into panic mode and required sedation.
So it turns out that it's NOT too late for the kids and I to join in on this little trip. Heh... *phew*
Except that while I blocked out all Steve's planning and trip details over the past couple of months, he made arrangements to leave on Thursday morning to go golfing in a neighboring city with a teammate. Which just means that I would have to drive to Vernon, alone with the kids on Friday. Which... I'm going to do. But I'm a little bit nervous. But kind of excited about the trip too. The hotel has a pool and free breakfast and we have a kitchenette and there are restaurants and a mall nearby. With a little luck the weather will be decent and we have have some fun.
My concerns are these -
~ the drive, alone with two little, bitty kids.
~ Lincoln's sleeping (I don't want to mess it up)
~ being stuck in the hotel room every night from 7pm on because kids need to go to bed.
~ sticking to my diet
~ getting obsessed with planning for the next week.
Anyone who has any tips, suggestions, tricks, assvice for me? I'm all ears.
3 comments:
- Eb 40+ said...
We just took the kids to the UK.
1) The car was great at getting the kids to nap
2) Stick to the sleep scheduale at all costs (the hotel may well give you a room for free for the kids??)
3)Diet - plan ahead but plan to treat yourself. Make it fun for you too :)
4)Plan for help - DH or family or service. I wish I had got a nanny from a website to help out for a few hours a days (not that I would leave them alone but help would have been amazing).
Take as much home "helps" as you can - toys, feeding tools etc. Especially stuff like DVD's that the kids watch or blankets and cribs sheets. Nothing worst than getting there and having to go shopping.
good luck!!
- May 11, 2011 at 3:44 PM
- noswimmers said...
Few pieces of assvice:
-put together a "play box" for the kids in the car. I throw some favorites, some ones he hasn't seen in a while, as well as a clipboard/crayons, and some books. Usually keeps him entertained for a while. If you have a portable DVD player, bring that too...my little dude was fascinated by it on our last trip...Baby Einstein!
-Bring a blankie for each kid, but don't wash it before you leave. Sleeping in a strange place can be tough, having a blanket that smells like home can really help
-Screw the diet (sorry, I'm no help with that)...I'm sure you'll be walking around/exploring lots!
-Will any of Steves buddy's be next door? If so, maybe you can party in their room and have a baby monitor?
...but most of all, have FUN! You deserve it. :)
- May 12, 2011 at 10:45 AM
- Candi said...
As far as the car ride, I have complete faith in you. I just took my kids to NY which is a 5 hour drive. My suggestion is 2 seperate DVD players and lots of snacks that don't involve sugar. Don't worry about getting there at a certain time...because you probably won't. If you need to stop and let them out of their seats to play for a few minutes, do it. You're a rockstar...you'll do great!
Have fun!!
- May 24, 2011 at 2:00 PM


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I am still looking for a ZX6E front fairing (can't find a decent one on ebay/the interwebs). I also made and added a spacer to the motorshaft and a shaft collar so now the sprocket is axially constrained on both sides and I dont have to depend on the set-screw/locktite for any constraint on the sprocket. I also got to use some sweeeeet new lathes (Proto trak) and after using them it will be extremely hard to go back to any other lathe.
|brand new brake pads and brake fluid!
|hacking into the tach
|using a function generator to hack the tach into showing me current
|the tach responds... now to hook it up to an arduino to show it in real time
I decided it was time to get into 3d printing so i decided to start printing some lug covers for the high current terminals on the controller and motor. After a couple of iterations I got a pretty satisfactory lug cover.
|v2 and 3 of the lug covers, more coming soon!
Next steps is to start wiring all the brake lights and turn signals. I might add a 12V battery and DC/DC to the system so that I dont have so drain all the power for auxiliaries from the sevcon. I am also trying to use as much of the old harness as possible (junction box, switches, connectors).


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Avossa's salary ranks 4th among heads of largest U.S. school districts
Palm Beach County Schools Superintendent Robert Avossa is the fourth highest paid superintendent among the nation's largest school districts and would earn nearly as much as the head of Miami-Dade County's public school system if he wins a proposed 3 percent pay raise, a new salary report shows.
School board members are scheduled to discuss a pay raise for Avossa Wednesday, three weeks after an earlier effort to hike his pay by nearly $10,000 was derailed by board members upset by the way the proposal was slipped onto their meeting agenda a day before the meeting.
UPDATE: We're hearing now that school board members are planning to postpone Wednesday's raise discussion once more – this time until February. The delay would give board members more time to study how other school boards structure pay raises for their superintendents.
Avossa became Florida's highest paid superintendent when he was hired last year at a $325,000 base salary. Board members at the time called the salary an important signal of the position's importance and their faith in their new hire.
Late last year, the Miami-Dade County School Board raised the base pay of its superintendent, Alberto Carvalho, to $335,000, making him the state's top earner. With more than 345,000 students, Miami-Dade's public school system is nearly twice the size of Palm Beach County's.
A new report prepared for board members by the school district shows that among the country's 11 largest school districts, Carvalho is the nation's third highest paid schools chief and that Avossa ranks fourth.
The report examines superintendents' base salaries and does not consider other forms of compensation such as bonuses, stipends and deferred compensation.
Both school chiefs vastly out-earn the leaders of the state's other large school districts: Broward, Orange and Hillsborough counties.
While superintendents of larger school districts tend to command higher salaries nationwide, the school district's study shows that is not always the case.
The top paid superintendent identified in the school district's report is Meria Carstarphen, the head of Atlanta's public school system, which with 55,000 students is less than a third of the size of Palm Beach County's. Her base salary is $375,000, according to the study.
By contrast, New York City's public school system – the nation's largest – educates more than 1 million students, but the report found its superintendent, Carmen Farina, earns a salary of just $227,727.
In his first annual evaluation, Avossa received top marks from school board members for his job performance. Last month's proposal to give him a 3 percent pay boost mirrored the pay increases received by teachers and other school district employees.
But as the school district's highest paid employee, Avossa's raise — $9,750 — would have amounted to more than five times the raises that teachers received, which maxed out at $1,715.
The proposal would have raised his total base pay to $334,750.
Last month some school board members said they believe at least part of his salary should be tied to his performance. They asked to postpone the decision on his raise until this month.
They are set to discuss the issue Wednesday but will not take any official action.
Editor's note: This article has been updated to reflect that the school district's study focused primarily on superintendent salaries among the nation's largest school districts.
Here's the complete analysis: