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Saint Joseph School Open House-Fairhaven
|Saint Joseph School
|100 Spring St.
|Tracy Travers
Please join us for our Open House and celebration of Catholic Schools Week. We will be providing tours on Sunday, January 28th from 11:30am to 2:00pm at Saint Joseph School, 100 Spring St. Fairhaven. We are in our 110th year of excellence in education and would love to show you why we promote Faith, Values, and Education and how you can afford a catholic education. For more information, please contact us at 508-996-1983 and visit our website at www.saintjosephschool.org
Like us on Facebook, too!
Saint Joseph School is a Catholic learning community devoted to the Sacred Hearts of Jesus and Mary and dedicated to providing a quality spiritual and academic education based on faith, values, and excellence that meets the needs of our students and their families.
We Offer: Pre-K, Kindergarten, Elementary & Middle
- Full day three- and four- year old Pre-school
- Breakfast Program and Before &
After School Care
- Full day Early Childhood Programs
- Safe and Caring Faith Based Environment
- Challenging Curriculum
- Character Development
- Family Events
- Small Classes Preschool Through Grade 8
- Community Service Projects
- Extended Care (2:30-5:30pm)
- Arts & Crafts, Lego Club, Glee
- Art, Music, Technology
Foreign Language,
Physical Education
- National Junior Honor Society

subset: commoncrawl


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If ever there was a time that a married couple needed the skills to fight against the power that would separate them, it is now. In no other place will you find the amount of helpful and practical information needed to get to the root of marital problems. You will learn the ultimate cause of why marriages fail and how to use specific tools to help correct behavior that is so damaging. This powerful, inspirational book helps you to see who is behind what you do. It will show you how to take more control over your life and to bring more happiness and joy into your marriage. You will have heaven on earth with your mate as you build unity that will endure forever. How to Build Marriage Unity That Will Endure Throughout All Eternity is an inspired work filled with practical examples of God-given tools. You will see yourself in these examples as you are enveloped in the spirit it teaches. Easy down-to-earth writing makes this book a joy to read as you learn some of the most important and valuable information you will need in this lifetime.Look, when you learned to drive a car, were you perfect at it just as soon as you got behind the wheel? ... I knew all the mechanics about how to drive a vehicle with a manual transmission which had a clutch and a three speed shift on theanbsp;...
|How to Build Marriage Unity That Will Endure Throughout All Eternity
|Kevan D. Austin
|iUniverse - 2009-05
You must register with us as either a Registered User before you can Download this Book. You'll be greeted by a simple sign-up page.
Once you have finished the sign-up process, you will be redirected to your download Book page.How it works:


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Discussion in 'Wii - Hacking' started by Aimen, Mar 23, 2009.
THANK YOU NinARM1!
Lol, how to avoid banning in a 10 minute video, which starts by using the twilight hack and which does not have a decription what it does...
I have 2 questions:
1. How are bans avoided in this tutorial?
2. Do gamers get banned, or only cheaters?
PS: "Boah is mir schlecht"(
damn cheating bastards. sorry for my harsh words but i could puke when i see ss like this.
ps.: that's what wiipower wanted to say with his german sentence.
Damn they are banning people now? I always had fun hacking on MKWii. But not to win, because there is no point. Just for fun and messing with people. I let them win.
So now I can't do this anymore? I would have to uninstall the HBC? Thats not gonna happen.
There is no confirmation claiming that having HBC installed is the source for the banning.
Good. But is there any way of getting around this yet? I'm assuming not?
Why would you ? Cheaters are lame, cheaters can't play. Cheaters play board games and tell you to look for the green elephant flying behind your back.
The HBC is NOT the reason for the ban, they are getting banned for cheating online, easy as that.
But all those cheaters don't want to see it's their fault so they blamed the HBC.
Some guy with no clue stated that nintendo would scan the hard disk of the wii for the HAXX ticket... seriously who would believe someone calling the NAND a harddisk ?
Once banned your can't access ANY WFC game stuff anymore, so better stop cheating online now, it's lame anyway...
Because I am a 4TL hacker and I do it for fun. Not to win. Cheating to win is cheap and I see no purpose in doing so.
only game i ever noticed cheats on while online was mario kart wii, and that wasn't often.
only game i cheated on was animal crossing city folk to take items from the store cuz i wanted a invisible chair(the chairs in the theater are invisible when you place them in your house, it's kinda cool)
can someone write a tut on how to get banned? Cause i've been trying my ass off to get banned, I dont like cheaters and dont normally cheat in online games, but for confirmation has to whats causing the problem, I been messing around with it, Have HBC installed and using mario kart, Cheating Online for about all Day? Now i'm not doubting people getting banned cause i know they are, its just i can't seem to get banned so i can't tell whats causing the banning So are they doing Wave Banning or what?
XFD @ people who think having the HBC gets you banned.
so what have you hacked then? i think your just an end user.
Nintendo has no way of scanning the nand that we know of.... There is obviously no code to do so in mario kart, or else they would have acted a lot sooner than now.
My guess is that there are no automatic procedures for banning someone. Someone at the big N probably looks at people who have a sudden huge boost in their win ratings online and then checks individual game logs to look for signs of cheating. That's probably why WiiBlaster hasn't been banned yet. He either hasn't had a huge spike in his win record, or isn't winning every single match even with cheats.
This doesnt affect those with Texture hacks right?
Custom Brawl Textures are too good!
Brawl Textures are just changed image files. v.v I don't think Nintendo will ban you for playing dress up with Brawl Characters, they can't see it anyways! They'd have to come over to your house and check your disc. xD
First of all, you create 2 topics. Second, kill yourself because hacking is bad mmkay.
banning cheating scum bastards ?
im all for that ..............well done nintendo


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Nick Diak will be performing an energetic acoustic set at Select Start Cafe this Friday evening, June 10th. The show begins 8pm.
Bio: Being raised in a musical family Nicholas Diak, aka Lumberjack Nick, grew up with much interest in music. It wasn't until a few years ago though that he started teaching himself guitar. Since then he's both written his own songs, and learned to play covers of popular songs that move him emotional. Over the past year he's begun teaching himself the craft of music recording and production with hopes of beginning to release his own singles later this year under the name "Watching and Waiting".
Come Join Us!


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Enter your details on the form or call 0844 598 3360.
For all other enquiries click here.
Please note that all fields marked * are required.
Enter your details on the form or call 0844 598 3360.
For all other enquiries click here.
Please note that all fields marked * are required.
|Villa - Détaché
|Salle(s) de bain
|Plage, Jardin, Panoramique, Mer
|Un parking souterrain
|Privé et communautaire
|Piscine intérieure chauffée, Communautaire et privé
|Surface construite
|205 m²
|Superficie terrasse
|441 m²
|Surface du terrain
|n/a m²
Hi all,
Just a quick note to say a massive thank you for all the help we received during our experience of buying a property with crystal shore. Liam was our guide from start to finish and and couldn't have been more patient and attentive if he tried! We were shown lots of different properties before deciding on our dream holiday home. We would definitely recommend your company, and feel we have made a good friend with Liam for life!!
Many thanks
Hi Jackie,
I would just like to thank you for your time & patience in showing me round the various properties. Also for taking the time to organize the meetings with the bank & lawyer, it was very much appreciated. Your help, advice & knowledge made the purchasing of a property so much easier & I am very happy with the purchase that I made. Once again many thanks for all your help & for putting up with me, it made a difficult decision a very easy & enjoyable one.
Many Thanks,
Hi Kim,
Hope you're well. We are off to Spain tomorrow to complete on our new house purchase.
Just a note to thank you and the team for selecting the perfect property in the perfect location.
Everything has gone well from the start. Please pass on our thanks to everyone in the Marbella office too.
Kind Regards
Dale & Cheryl


text: Woe Is I: Pronouns and Case 63 Sorry, Wrong Number What should you say on the phone: "It is me?" or "It is I?" Maybe you should just hang up the phone and send a fax. The rivalry between "It is me" and "It is I" is right up there with Pepsi and Coke battling for market shares. The "It is I" camp argues that forms of the verb to be, such as is and was, should be followed by pronouns in the nominative case. Therefore, here the pronoun would be I. On the other hand, the "It is me" camp counters with the argument that noun case in English has disappeared. Further, they contend that the pronoun case has become so weakened that the force of word order now overrides the force of case. The placement of the pronoun in the object part of the sentence "It is me" and "It is us" has become increasingly acceptable as standard usage even in boardrooms. But if you're speaking with a lan- guage purist who is likely to become offended by today's more relaxed standards of speech and writing, use the time-honored "It is I" instead of "It is me." Strictly Speaking Should the childhood mecca be "Toys R We"? Should Sammy Davis Jr. have sung "I Gotta Be I"? (According to grammar frumps, yes!) Seventh-Inning Stretch Stand up, wave your arms around wildly, then sit a spell and take this brief quiz. Score yourself,


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No distribution's installer makes setting up disk encryption as easy as Anaconda, the Fedora system installer. And that has not changed in Fedora 16, the latest stable release. On previous versions of Fedora, those released before Fedora 16, the only automated disk partitioning option was one based on LVM, the Linux Logical Volume Manager. That made it easy to install Fedora on encrypted LVM partitions.
But it also meant that if you wanted to install Fedora on encrypted, non-LVM partitions, Anaconda offered no automated option. That is no longer the case in Fedora 16.Full story »


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SEASONAL CAMPAIGN A/W 2015 – The Genuine Icon
With an extended offer of apparel and menswear to their already renowned shoe and leather goods business, Aquila approached us to develop a campaign that would help position their business and set a trajectory around which we could build a dimensional campaign.
Shooting with English photographer Ben Weller, the legendary Werner Schreyer, the face of men's fashion synonymous with style since the early 90's represents the legacy of the brand, its timeless designs and dedication to genuine character. Intelligent, confident and masculine, Werner not only provided great PR dimension, but encapsulated an interesting and memorable personality that embodied the character of the Aquila man.


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Academic Advisors
Upon admission to TSU as a matriculated student, you will be assigned an Academic Advisor. Your Academic Advisor is responsible for guiding you through the initial stages of your degree program and thereby facilitating your successful completion of it. He or she will be your primary resource for counsel in regard to contemplated changes to your program and any other academic issues that may arise.
While the assignment of an Academic Advisor will be made by the Dean of Admissions & Enrollment based on faculty availability and perceived areas of common interest, we invite your suggestion. To the maximum extent possible, we will attempt to accommodate your preference.


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Our partners are the most critical component to our success – they live and work in ConnectWise every day. To become as efficient and productive as possible, solution providers often need specific functionalities from other tools they use to be integrated with ConnectWise. With the help of Mobius Works, you will be able to quickly and easily integrate your application to ConnectWise for a robust solution.
Our integration partners enjoy numerous benefits, including:
- The ability to communicate and share information between key systems
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- Time and money savings
- A smoother, faster business operation and better utilization of resources
For more information, email our Certified ConnectWise Development Team, or check out our ConnectWise Marketplace listings:


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Multiple locations in Roseville will be open and serving as cooling centers this week; including three libraries and the Salvation Army.
The Salvation Army of Roseville will be open until 6 p.m. Monday, providing snacks and bottles of water for those who need help.
Also, the city is extending the hours of their libraries to provide a cool place for residents. The downtown location on Taylor Street will be open until 8 p.m. Monday through Thursday, and until 7 p.m. on Friday.
The Maidu Library and Martha Riley Community Library will be open until 7 p.m. Monday through Wednesday and closed on Thursday for the July 4 holiday.


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Inexact hardware design, which advocates trading the accuracy of computations in exchange for significant savings in area, power and/or performance of computing hardware, has received increasing prominence in several error-tolerant application domains, particularly those involving perceptual or statistical end-users. In this paper, we evaluate inexact hardware for its applicability in weather and climate modelling. We expand previous studies on inexact techniques, in particular probabilistic pruning, to floating point arithmetic units and derive several simulated set-ups of pruned hardware with reasonable levels of error for applications in atmospheric modelling. The set-up is tested on the Lorenz '96 model, a toy model for atmospheric dynamics, using software emulation for the proposed hardware. The results show that large parts of the computation tolerate the use of pruned hardware blocks without major changes in the quality of short- and long-time diagnostics, such as forecast errors and probability density functions. This could open the door to significant savings in computational cost and to higher resolution simulations with weather and climate models.
1. Introduction
Despite steady increases in the performance of state-of-the-art supercomputers, the available computing resources still cannot satisfy the demand for computational power. For some time now, the main increase in FLOPS1 of today's computing centres is not so much caused by an increase of performance of a single processor, but rather by an increase of the number of processors that run in parallel. The work with 106 or 107 processor cores in one supercomputer brings several challenges for both the development and use of high-performance computing facilities. Two main challenges are the high energy demand and error-resilience. Plans to build a computer capable of 'exascale' performance (approx. 1018FLOPS) warn both that 'traditional resiliency solutions will not be sufficient' and that typical power supply limits (of about 20 MW) will not be met [1].
The increasing costs of power are beginning to force hardware developers to rethink some of the principles of computing. One candidate is to trade high precision or even the reproducibility of computations for reduced energy demand and/or higher performance. Over the past decade, a variety of approaches have been proposed to take advantage of the error-resiliency in several current and emerging classes of applications, in particular media/signal processing and recognition, mining and synthesis. These approaches advocate trading the accuracy of the underlying hardware fabric in return for significant savings in the hardware resources used such as energy, delay, area and/or yield and, therefore, lead to a reduced cost for computing. Dubbed inexact [2] or approximate computing, this work has now led to a subfield of active research spanning methodologies that exploit the fact that, quite often, applications do not need to have precise outputs. Taking advantage of various inexactness-inducing 'knobs' to vary the hardware quality at different levels of hardware design abstraction, our own work has shown that these inexact methodologies could result in significant resource savings in exchange for entirely tolerable accuracy trade-offs. The feasibility of these resource–accuracy trade-offs has been successfully demonstrated in several key resource-intensive arithmetics and digital signal processing primitives [3,4].2
Several techniques at different levels of hardware design abstraction have been proposed to realize inexact hardware. Physical/circuit-layer techniques such as voltage overscaling and its variants have been the popular choice in the beginning to induce inexactness [5–7]. Later, owing to the ease of hardware realization, inexact techniques moved towards higher levels of abstraction such as the logic/architecture layers [4,8]. In this paper, we focus on one of these inexact design techniques, probabilistic pruning [8], that, apart from its implementation ease, has been shown to achieve significant gains in all of energy, delay and area in exchange for tolerable amounts of accuracy loss demonstrated in the context of integer arithmetic units. However, in order to extend and explore the inexact design techniques to a broader milieu of computing encompassing general-purpose processors and high-performance workloads, this existing work on pruning would require the extension to floating point units, an aspect that has not received much attention so far.
The weather and climate modelling community is a heavy user of high-performance computing, and weather and climate models run on supercomputers that are among the fastest in the world. Even so, the model resolution is far from being adequate [9] and limited by the available computing power. An increase in computational power would allow higher resolution simulations and produce higher quality weather and climate predictions.
A recent study [10] investigated the use of inexact hardware in weather and climate modelling. Faulty or low precision hardware was emulated within simulations of a simple atmosphere model based on spectral discretization methods to investigate the sensitivity of various components of the model to hardware-induced errors. The study revealed that large parts of a model integration can be computed on inexact hardware without serious penalties, provided the sensitivities are respected, for example by using low precision for small-scale dynamics and high precision for large-scale dynamics [10].
It is the aim of this paper to initiate a successful cooperation between the two scientific communities of inexact hardware development and weather and climate modelling. We expand previous studies on pruning techniques to floating point arithmetic units (FPUs). These pruning techniques are used to design FPUs with a wide range of accuracy degradations. We test the applicability of this hardware in atmospheric modelling by emulating the use of the pruned hardware in simulations of the Lorenz '96 model, a toy model for atmospheric dynamics, and test the sensitivity of different parts of the model to reduced precision FPUs. The emulation is configured by measuring error patterns of the FPU designs for inputs typical of the Lorenz '96 simulations. The results of these simulations are used to further refine the hardware designs, increasing or reducing the errors as allowed or required. This iterative design loop was repeated several times. We wish to emphasize that throughout this paper, we might use the word hardware for convenience to refer to simulations of synthesized versions of FPUs as opposed to fabricated integrated circuits.
We present results for simulations with 10 FP adder–subtractor and 10 FP multiplier blocks and list the expected savings for area and power consumption and the increase in performance compared with a precise double precision FPU for each set-up. After preliminary tests for which we compute only one subroutine of the model with the emulated pruned hardware, we decide on four combinations of FP adder–subtractor and multiplier blocks that are used to identify the sensitivities to hardware faults of the different parts of the model. Finally, we try to simulate as many parts of the model as possible without serious penalties.
Section 2 gives details on pruning and the development of pruned FPUs with reasonable error rates. Section 3 provides a detailed description of the Lorenz '96 model and the emulator which mimics inexact hardware. Section 4 presents the derived hardware set-ups that are simulated, the results of numerical simulations and a cost estimation for the different simulations.
2. Inexact hardware design
Here, we describe the methodology for the design of the inexact FPU. As this paper is meant to be a first approach only, we limit ourselves to a simple inexact design technique to demonstrate the utility of such inexact hardware for the targeted atmospheric modelling application and defer the exploration of more complicated approaches involving the usage of multiple inexact design techniques from different layers of design abstraction simultaneously [11] to future papers. As mentioned in §1, we chose probabilistic pruning [8] as our inexact technique given its ease of implementation and the ability to provide zero hardware overhead realizations. The pruning algorithm is revisited in §2a and its usage in the context of FPUs is described in §2b.3
(a) Methodology for inexact design
The main idea behind pruning is to reduce the size of a hardware architecture by removing parts that are hardly used or do not have a significant influence on the calculations. We consider a circuit that implements a floating-point binary operation (such as addition or multiplication). This circuit consists of logic gates connected by wires, with each gate accepting (binary) inputs and producing (binary) outputs. Our probabilistic pruning algorithm [8] operates by building a directed acyclic graph of the circuit with nodes denoting a gate or a collection of gates and edges denoting the interconnections. It then annotates each of the nodes in the circuit with analytically or empirically derived significance and activity values. The significance value quantifies the impact of a node on the accuracy of the circuit. A node which is only connected to a least significant bit of the output has a lower value than a node connected to a bit of higher significance. To this end, the significance value depends on the circuit topology. The activity value denotes the number of times the output(s) of a node switch between the two possible binary values (a 0 or a 1). The activity value, to some extent, depends on the application being run, for example if input values of a specific node are biased towards either 0 or 1 for the given application. Using these annotations on each of the node as a basis, the pruning algorithm proceeds through two main steps:
Ranking phase. In this step, each of the node in the circuit is ranked (in the order to be pruned) using a function of the significance and activity values. We choose the significance-activity product (SAP) as a basis for ranking the nodes. In our usage, the nodes with higher SAP values receive a lower rank (hence, lower likelihood of being pruned away).
Pruning phase. Equipped with the desired error metrics, the pruning step works on deleting the nodes in the circuit that have the highest rank. In this step, we use the knowledge we have on the statistics of the activity of each node. If one of the input values is very likely to be observed at the output of the pruned node, then we use a greedy4 substitution.5
Once we have reached the targeted error bound,6 we re-synthesize the circuit to eliminate any redundant logic and evaluate the resource savings achieved as a result of this trade-off.
(b) Implementing an inexact floating point unit
The most important aspect of pruning involves the annotations of the node with the significance and activity values. Hence, in order to better configure the inexact hardware for the targeted application, we require input traces that capture the statistics of the application and guide the pruning algorithm. In this paper, as we are targeting the arithmetic units with regular structures that stay fairly generic, we use the output significance level to determine the significance of the nodes (similar to earlier works on inexact adders [12]), i.e. nodes connected to the most significant bits of the outputs receive higher significance values.
In this paper, we extend previous work [8] to include the FPU. We applied pruning in the significand. To enable the pruning techniques, and in order to simulate inexact behaviour of different architectures, we designed a bit width parametrizable (up to 64-bits—double precision) FPU which is compliant with the IEEE-754 standard [13] using VHDL/Verilog hardware description languages. The FPU co-processor architecture is composed by a dual pipelined execution unit, (i) for addition/subtraction operations, and (ii) for multiplication operations. Thus, each double precision addition/subtraction operation can be executed in parallel with each multiplication. The architecture is similar to the approaches presented in references [14,15]; however, in this work, the design of the FPU has been optimized to combine high-throughput with low-latency (one cycle latency for each operation).
Within the FPU, the 57-bit integer adder and 53-bit integer multiplier are the most computationally intensive blocks and hence we apply the pruning algorithm on these blocks as a basis for our preliminary investigation. In this paper, we use the Kogge–Stone parallel prefix adder7 and truncated array multiplier architectures [17] in the FPU.
Data from simulations of the Lorenz '96 model were used as input application traces for the annotations needed by the pruning techniques as described in §2a. We show the input traces of the integer adder and multiplier units used in our FPU in figure 1. The x-axis refers to the bit positions of the input bits of the 57-bit adder and 53-bit multiplier (e.g. the number '57' on the x-axis of the integer adder refers to the input most significant bit of the adder, whereas '1' refers to the input least significant bit. The y-axis corresponds to the probability that a bit-position has no transition activity when an application trace is run on it (e.g. a value of '0.5' implies a probability of 50% for a transitions between or , whereas a value of '1' implies that there is no-transition activity in that input bit and it is either a constant '0' or a '1').
As evident from the figure 1, both the adder and the multiplier inputs have a relatively uniform input activity profile across all the input bit positions (one striking difference is the low activity profile of one of the inputs to the multiplier which provides a scope for more aggressive pruning), which puts the onus on the significance values to guide the pruning algorithm. As we use an output significance-driven assignment, the pruning algorithm is likely to converge to bit width reduced blocks as the initial candidate solutions.
In the interests of saving time during pruning and in order to reduce the design space exploration, we start with an initial bit-width-truncated configuration, rather than with pruning from the beginning.
We therefore use the two-step heuristic method identified below.
(i) Apply a coarse-grained bit width truncation on the complete circuit graph of the integer adder and multiplier (in this paper, we have used a decreasing step size of 8) and evaluate the application level quality for the obtained designs.
(ii) We then identify the bit-width-truncated circuits, which are closer to the application's error-tolerance threshold, and use them as a starting point to apply the logical pruning algorithm on these reduced circuit graphs to achieve a fine grain exploration and enhance the resource savings further. We term this step as logic pruning (LP) which executes the two-step ranking and pruning phases described in §2a on the reduced circuit graph annotated with the input traces from the application.
The derived hardware set-ups are then tested within the Lorenz '96 model. If the simulations reveal that the errors can be larger, or should be smaller, then the procedure is repeated with adjusted level for the truncation. Several iterations of this process were done for this paper, to reach the optimal hardware set-up. A sketch of the framework and the proposed methodology is presented in figure 2.
3. The Lorenz '96 system
The complexity of8 a full weather or climate model together with the need to emulate hardware which is not yet realized as 'hardware' prevent us from working with a full weather or climate model. Even restricting ourselves to the dynamical core9 of a working model would be a major undertaking. Therefore, we consider a toy model of atmospheric dynamics—the Lorenz '96 model. The Lorenz '96 model was proposed in reference [18] and consists of two sets of prognostic variables. The 'X'-variables represent large-scale dynamics of the global atmosphere. These are the quantities we want to predict correctly in global weather and climate simulations. The 'Y '-variables represent small-scale dynamics of the system that couple to the large-scale variables.
Owing to the coupling of the large- and small-scale variables and the nonlinear behaviour, the Lorenz '96 system displays multi-scale and chaotic properties that are features of many components of atmospheric dynamics, such as convection, at least to some extent. The system is heavily used to test conceptual ideas for example for data assimilation or parametrization schemes in atmospheric modelling, before complex, global circulation models are investigated [19–22].
(a) Equations
The large-scale variables form a one-dimensional periodic space. Each large-scale variable couples to a set of small-scale variables that forms a one-dimensional periodic space on its own. We use eight large-scale variables Xk (Xk−8=Xk=Xk+8), and 32 small-scale variables Y j,k (Y j−32,k=Y j,k=Y j+32,k) for each Xk.
The Lorenz '96 system is described by the following set of equations 3.1and 3.2where we use h=1, c=10, b=10 and F=20. We use a fourth-order Runge–Kutta scheme to integrate the model in time. For this scheme, the right-hand side of the equations (3.1) and (3.2) needs to be calculated four times per time step, which generates a large part of the computational cost. The size of the time step is 0.0005 model time units. It is generally accepted that one model time unit of the Lorenz '96 model corresponds approximately to five atmospheric days.10 We compare the results of simulations with the full system with results of a reduced system for which the small-scale variables are parametrized (the deterministic scheme in reference [23]): where U(Xk) tries to mimic the behaviour of the Y variables and a1=−0.00235, a2=−0.0136, a3=1.3 and a4=0.341.
Because the parametrized system has only eight degrees of freedom (compared with the 264 degrees of freedom of the full model), it is much cheaper and can therefore serve as a lower limit for the forecast quality. Simulations with the full system on emulated inexact hardware should always show a higher quality compared with the parametrized system.
(b) Emulator for inexact hardware
To develop meaningful emulators for the different set-ups for inexact hardware, simulations of the full, unperturbed Lorenz '96 system are performed and the minimal and maximal values of the input variables for each operation, for which reduced precision is emulated, are measured. Afterwards, the two-dimensional space (one-dimensional if one of the input variables is a constant) between the minimal and maximal values of the two input values of a specific operation is discretized into a grid with 50×50 grid cells. To set up the emulator, we need to assign a specific error value for input variables that fall within a specific grid cell of the grid of input variables. To this end, we calculate at least 20 sets of random input variables that fall within the range of each grid cell and calculate the error each hardware set-up would show for the sets of input variables, using the hardware simulator. Out of the error values calculated for each grid cell, the largest error that is present is stored in a table for which each entry belongs to a specific grid cell. We create such a look-up table for each operation and each hardware set-up. If the emulator is used to mimic the use of a specific inexact hardware for a specific operation within simulations of the Lorenz '96 model, then the error that is stored in the corresponding look-up table is added to the result of the operation, if the input variables fall into a given grid cell. If the inputs to an operation fall outside of the range of the look-up table the largest error from the entire table is added. To this end, the emulator represents a kind of worst-case scenario for the error induced by the imprecise hardware.
It is known from reference [10] that the calculation of the right-hand side of the small-scale variables is quite forgiving when processing errors are included.11 First tests therefore calculate the right-hand side of equation (3.2) on the emulator.
The multiplications that involve constants in equation (3.2) can be done before the time integration is started. When calculating c1=−cb, c2=−c and c3=hc/b in advance, we end up with the following seven consecutive operations that are necessary to calculate the right-hand side of equation (3.2), of which three of them are addition or subtraction, and four of them are multiplications:
(i) r1=Y j+2,k−Y j−1,k,
(ii) r2=Y j+1,k⋅r1,
(iii) r3=c1⋅r2,
(iv) r4=c2⋅Y j,k,
(v) r5=r3+r4,
(vi) r6=c3⋅Xk and
(vii) dY j,k/dt=r5+r6.
Traces of these operations are used to determine the activity values for pruning.
Figure 3 shows the error pattern for two operations with one constant input variable for the derived hardware and the emulator. It can be seen that the magnitude of the error is changing stepwise when the exponent of the FP is changing. This is what we would expect when bit width truncation is used.
Eventually, the whole model was put onto the emulator, performing the same steps for each operation as before.
4. Results
We present the developed FP architectures in detail and test the quality of the different set-ups when calculating the right-hand side of the equation for small-scale variables in Lorenz '96 with emulated errors. We discuss the results, characterize the perturbations and decide on four reasonable combinations of adder–subtractor and multiplier blocks for further investigations. These combinations are used to calculate different parts of the code on emulated inexact hardware, to evaluate the different sensitivities to inexact hardware. Finally, we run short- and long-term simulations using different hardware combinations in the different parts of the code as benchmarks, compare the results with precise and parametrized simulations, and discuss possible savings.
(a) Inexact hardware structures
In table 1, we compare the synthesis results of the pruned FP architectures with the conventional exact FPU using the Nangate 45 nm Open Cell Library (v. 1.3 [24]; slow corner).12 We have pruned the adder–subtractor and multiplier integer blocks in different ways. The target is to provide the reader with trends and associated trade-offs, in terms of area, power, performance and impact on the simulation.
As expected, with the approach presented in this work, we can achieve between ≈16% and 66% reduction in energy consumption, with corresponding delay and area reductions between ≈2–34% and ≈15–70%, respectively, for the pruned adder–subtractor blocks (i.e. A1–10) w.r.t. the exact implementation. On the other hand, for the pruned FP multiplier blocks (i.e. M1–10), we can achieve energy reductions between ≈23% and 93%, with corresponding delay and area reductions between ≈2–59% and ≈25–94%, respectively. Of course, all savings are at the cost of losing precision when computing FP operations. For instance, in the A6 architecture, the reductions are ≈66%, ≈70% and ≈26% in terms of power, area and performance, respectively, with an associated relative error between 7.6138×10−10 and 6.8555×10−01. By contrast, in the M10 architecture, the energy and area is reduced by ≈94%, with the corresponding performance improvement of ≈59%, with a relative error bounded from 2.4629×10−07 up to 1.8180×10−01.
The forecast errors in table 1 refer to the mean, absolute error of the large-scale variables compared with a control simulation on precise hardware. We simulate 5000 short-term forecasts with the Lorenz '96 model with emulated inexact hardware using the control simulation for initialization. The forecasts are started in intervals of 10 model units of the control simulation. For the FP adder–subtractor or multiplier blocks either the three sums and subtractions or the four multiplications necessary to calculate the right-hand side of the short-term variables (see operations (i)–(vii) in §3b) are calculated with emulated errors for the respective inexact hardware.
We evaluate the average forecast error for the large-scale variables after one model time unit (2000 time steps) when comparing to the control run. The forecast errors are increasing with increasing maximal and mean hardware error, as expected. The adder–subtractor blocks with logic pruning produce large forecast errors and even model crashes (for A9 and A10). We attribute this to the inherent set-up of the emulator as it pessimistically adds the largest observed error over an application test bench run to every inexact computation in the emulator to account for the worst-case scenario. This pessimistic approach naturally favours inexact techniques which limit the worst-case errors (e.g. bit width truncation) as opposed to those which lower the average case errors (e.g. logic pruning) as identified in reference [4]. We hope to remedy this, in future work, by injecting observed error distributions in the emulator rather than in worst-case errors. However, the multiplier with logic pruning allows results that are much better.
Figure 4a shows the forecast error plotted against the maximum and the mean relative error of the used hardware. In a rough approximation, the forecast error behaves proportional to the relative error of the simulated hardware to the power of one third (see the ∼x1/3 function in figure 4a).
The different FP adder–subtractor and multiplier blocks in table 1 can be combined arbitrarily, to form a full FPU. We decide on combinations based on the forecast errors after one model time unit that have a similar range. We consider four combinations of FP adder–subtractor and multiplier blocks in the rest of this paper which are listed in table 2. In a first test, we apply these combinations independently to three different parts of the model.
(i) To calculate the right-hand side of the equation for small-scale variables (equation (3.2)).
(ii) To calculate the full dynamics of the small-scale variables (equation (3.2)).
(iii) To calculate the full dynamics of the large-scale variables (equation (3.1)).
Figure 4b,c shows the forecast error against time for the different architectures used in the different parts of the model. Given that a model time unit corresponds to approximately five atmospheric days, all simulations in figure 4 appear to have an error that is reasonably small, except for the simulations in which H2, H3 or H4 are used to calculate the large-scale variables. In these simulations, the forecast error is smaller on the long term, because the heavy change in the dynamics of the system leads to a smaller difference for uncorrelated perturbed and unperturbed systems, compared with the difference between two uncorrelated, unperturbed systems. As expected, the error is smaller for part (i) compared with part (ii) when different imprecise architectures are used.
(b) Benchmark simulations with Lorenz '96 on inexact hardware and discussion of possible savings
Based on the results of the §3a, we perform one simulation for which the H1 architecture is emulated for the whole model integration and three simulations for which the dynamics of the small-scale variables are calculated with the H2, H3 or H4 architecture, whereas the large-scale dynamics are calculated with H1. We use these set-ups to calculate the forecast error in short-term simulations as before and perform additional long-term simulations. We simulate each set-up for 100 000 model time units after spin-up for the long-term simulations.
Figure 5 shows the results for forecast errors against time for the short-term simulations (figure 5a), and the probability density function (PDF; figure 5b) and spatial and temporal correlation (figure 5c,d) of the Xn values for the long-term simulations. The forecast errors for all simulations with inexact hardware are reasonably small, given that a model time unit corresponds to approximately five atmospheric days in terms of predictability and that the quality of a typical weather forecast is declining fast beyond a couple of days of a forecast. For all diagnostics, the simulations with emulated inexact hardware give better results than the simulations in which the small-scale dynamics are parametrized.
We calculate the Hellinger distance, H, as a measure of the difference between two PDFs: 4.1where p(x) is the PDF of the imprecise or parametrized simulation, whereas q(x) is the PDF of the control simulation. Table 3 lists the mean of the Xn values and the Hellinger distance for the different set-ups.
In summary, the simulations with H1 show that the full model can be calculated with simulated hardware that has 54%, 49% and 16% savings in area, power and delay for the FP adder–subtractor block and 76%, 75% and 22% savings in area, power and delay for the FP multiplier block without serious penalties. When profiling a model simulation of the full Lorenz '96 model on precise hardware,13 it turns out that about 75% of the computational cost, in terms of execution time, is caused by the calculation of the small-scale dynamics, about 19% is caused by the calculation of the large-scale dynamics and about 6% is caused by output and model coordination. The errors stay reasonably small for the set-ups H2, H3 and H4. We therefore conclude that about 75% of the computational cost for the control simulation, in terms of execution time, could be put on hardware that has up to 70%, 66% and 26% savings in area, power and delay for the FP adder–subtractor block and 92%, 92% and 19% savings in area, power and delay for the FP multiplier block.
5. Conclusion and future directions
In this paper, we demonstrate the potential utility of inexact hardware for atmospheric modelling. The results show that the Lorenz '96 model can tolerate the use of inexact hardware in large parts of the model integration without major changes in the forecast quality of weather- and climate-type diagnostics, while benefiting from substantial reductions in the power dissipation and area of the FPU, and improvements to hardware performance. Our results suggest that the motivation behind this paper—to use very efficient but inexact hardware to potentially cope with the ever-increasing power consumption of state-of-the-art supercomputers for modelling weather and climate—is worth investigating and has the potential to lead to a new class of models and hardware for computational fluid dynamics.
The simulations with Lorenz '96 confirm the result in reference [10] that the different parts of a model for atmospheric dynamics have very different sensitivities to hardware errors. Approaches that take care of the different sensitivities, such as scale separation, are crucially important when calculating a weather or climate model on inexact hardware. Our results suggest that large parts of the Lorenz model can cope with strong errors. However, the Lorenz model is no more than a toy model and can be assumed to be fairly forgiving in terms of inexactness, because it has relaxation terms and a natural scale separation which is not apparent in full atmosphere models. Further tests are needed to verify that an application of inexact hardware to small-scale dynamics of a high-resolution weather or climate model has no negative influence on large-scale dynamics. Further tests are also necessary on the influence of hardware errors on conservation and convergence behaviour and on the sensitivity of different discretization schemes in time and space to hardware errors. The hardware is neither produced nor tested in great detail yet, and the emulator used is still rather crude.
The technique of pruning used in this paper is a relatively easy approach to obtain inexact hardware set-ups with high savings in area, power and performance. While the combination of bit width truncation and logic pruning seems to have already achieved substantial savings (compare M7–10 with M6 in table 1), we anticipate that applying cross-layer inexact techniques through a co-design framework on the lines of reference [11] would further boost the resource savings. As mentioned in §4a, the current emulator pessimistically adds the worst-case error observed over a set of test vectors to every computation involving the inexact FPU and hence is inherently biased against the inexact techniques that minimize average error while allowing a small number of fairly large errors. We need to refine the emulator to add the appropriate error distribution as opposed to a single worst-case error value in future work.
We plan to conduct more studies on how to gracefully and efficiently integrate exact and inexact hardware and how to load balance the different parts on parallel machines. Approaches to trade-off exactness against a reduced energy demand should be extended to memory and data storage, because memory bandwidth is a major bottleneck for many atmosphere models. Future work will focus on the use of inexact hardware in larger models, such as the dynamical core of an atmosphere model. To this end, the development of inexact hardware and an appropriate test set-up needs to go hand in hand. A strong cooperation between hardware developers and users is essential.
Funding statement
Hugh McNamara is supported by the Oxford Martin School (grant no. LC0910-017), the position of Peter Düben is supported by an ERC grant (Towards the Prototype Probabilistic Earth-System Model for Climate Prediction, project reference 291406). This work was also partly supported by the ERC grant ref. 2009-adG-246810 funded by the European Community.
We thank Fenwick Cooper and Hannah Arnold for help with the numerical simulations. The idea to write a paper on the use of pruned hardware in Lorenz '96 developed during a meeting of Peter Düben, Hugh McNamara, Krishna Palem and Tim Palmer. Peter Düben performed the numerical simulations, developed the emulator for pruned hardware and wrote large parts of the paper. Jaume Joven designed, simulated/verified, synthesized and integrated all hardware blocks, elaborated the error pattern from Lorenz 96 traces, and contributed to the writing of §§2 and 4. Avinash Lingamneni provided the framework and the algorithms used to produce pruned integer adder and multiplier hardware blocks, and contributed to the writing of §§1, 2 and 5. Krishna Palem was the bridge between the error analysis work and the inexact computing effort, respectively, at EPFL and Oxford. Giovanni de Micheli provided useful feedback on the writing and coordinated with Krishan Palem the hardware side of the presented framework.
One contribution of 14 to a Theme Issue 'Stochastic modelling and energy-efficient computing for weather and climate prediction'.
↵1 The performance in high-performance computing is often measured by the number of floating point (FP) operations per second (FLOPS). Today's top supercomputers have performance measured in tens of petaFLOPS—1016FLOPS.
↵2 Inexact computing has since grown as an area of study and innovation, and several papers have been written by a variety of groups including ours; we are citing only those papers that are directly relevant to the techniques used in §2 to induce inexactness in the floating point units, and the reader is referred to the general literature for additional reading on this rapidly evolving area.
↵3 The authors acknowledge that there is no novelty in the inexact method of choice (probabilistic pruning) in this paper obtained from reference [8] including the scope of its use to the integer unit which constitutes computing the mantissa part of the floating point unit only. However, the novelty is in evaluating the impact of this inexact technique with the overall architecture of a floating point unit in terms of the savings achieved, and its eventual impact on the application level quality in the Lorenz '96 application (described in §3).
↵4 A 'greedy algorithm' refers to making the locally optimal choices at each step in the hope of finding a global optimum solution. In this context, we are using such a 'greedy' approach by substituting the output of a node that is marked for pruning with its most observable value (a 0, 1 or one of the node's inputs) determined through the annotations.
↵5 This step also includes the healing phase of the pruning algorithm in Lingamneni et al.[11].
↵6 The targeted error bound is determined by the application. In the case that there is no well-quantified error bound, we impose a range of artificial error targets on the pruning algorithm and use the resulting inexact pruned circuits in the application to estimate the error tolerance bounds.
↵7 A Kogge–Stone adder is a hardware design which is used frequently for sums of binary numbers in state-of-the-art computing [16].
↵8 The application-specific integrated circuit (ASIC) design flow consists of a methodology and associated sets of tools to synthesize/generate, validate and test hardware architectures. These tools offer the possibility to estimate area, power and performance (circuit delay) before manufacturing the final integrated circuit.
↵9 The dynamical core refers to the portion of the code that involves fluid dynamical behaviour, without the influence of moisture, clouds, ice and other physical processes and forcings which are dealt with in the 'parametrization' portion of the model.
↵10 The error growth after one model time unit in Lorenz '96 was estimated to be similar to the error growth in a numerical weather forecast after 5 atmospheric days [18]. However, this number needs to be reduced slightly nowadays, because the forecast quality of weather models has improved (Hannah Arnold 2013, personal communication).
↵11 A fairly crude emulator that induced random bit flips of one of the bits of the significand into the result of 20% of all FP operations was used to calculate the right-hand side of equation (3.2) without a serious reduction of the quality of the results for large-scale variables in long-term simulations.
↵12 In this work, we use the slow corner of the Nangate 45 nm Open Cell Library (SlowSlow process, voltage =0.95V and temperature =125°C) in order to obtain the area, power and performance measurements.
↵13 Using the gnu profiler gprof and the Intel Fortran compiler with O3 optimization, and running the code on an Intel i7 CPU.
© 2014 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the original author and source are credited.


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2017 Audi R8
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Bet You Didn't Know: Secrets Behind the Making of "House Party"
*Smiles Profusely* I don't know about you but just the mention of House Party is guaranteed to put a huge grin on my face. At a time when movies like The Breakfast Club and Ferris Bueller's Day Off were making a killing at the movie theaters, the black community was waiting for that same type of good-natured flick. You know, the type of movie where we could see young black kids having fun, where the only real threat to their lives was catching a butt whooping instead of a bullet. That's what House Party did for us. It showed us the fun side and honestly made us feel lucky to be young and black. We needed this movie and we needed it to be well done. Luckily, with the combination of a talented cast, hilarious one liners, great music and a little bit of romance, we got just that.
The music gets you hype, you still do the dance with your homegirl and the DVD is on the shelf right now, but you probably don't know these the behind the scene secrets. Check them out.
Who's the director?
Reginald Hudlin was fresh out of college when his film was picked up by New Line Cinema. House Party was actually the film he wrote as his senior thesis at Harvard. Inspired by the rise and influence of Hip Hop in popular culture, Hudlin said he wanted to write a movie that incorporated this art form. He also originally wanted the film to encourage kids to use condoms to combat the AIDS epidemic that was on the rise in the early to mid '80's. The film was popular on campus and eventually it caught the attention of a junior executive at New Line Cinema.
The Fresh Prince and DJ Jazzy Jeff were supposed to play the lead roles
When it came time to cast the movie, it only made sense that it would involve Hip Hop stars. And Will and Jazzy Jeff owed New Line Cinema a favor…like legally. In their single, "Nightmare on My Street" they sampled Freddy Kruger from the similarly titled horror film "Nightmare on Elm Street." They came with a settlement and a part of it was for Will and Jazzy Jeff to appear in a New Line film. The studio suggested them to Hudlin. Hudlin had his reservations, saying he didn't want them to do the film out of obligation. Not completely ruling it out, he talked to Russell Simmons about it. Simmons said that the two had another movie they were working on and said no. So that's how they opened up the casting. As you might have imagined, the Fresh Prince Jazzy Jeff movie never happened.
How did Kid-N-Play come into the picture?
Christopher "Kid" Reid and Christopher "Play" Martin were originally background dancers for Salt-N-Peppa. When they first started rapping they were called The Fresh Force Crew. Maybe Salt N Pep inspired them to take on the "N." Wherever it came from, it was a good decision. They got the role because Hudlin was a fan of Kid'n Play's music and just so happened to know people on their management team. He asked the team about their work ethic and heard nothing but good things, so he approached them with the deal. Although, they had the option to go on tour, the two took the movie deal and made history.
The Dance
Now that you know that Kid 'n Play used to be background dancers it's not hard to see how they were able to break it down for this movie. The Kid 'n Play kick-step was already a part of their schtick. So naturally, it showed up in the film. As for the girls, actress A.J. Johnson, who played Sharane, Sidney's friend, wasn't too bad of a dancer herself. She choreographed the girls' portion of the routine. Not bad, eh?
And since I'm all about saving you some time, I've included the video below because who can ever get enough of it?
Robin Harris
It's terribly sad what happened to Robin Harris. A comedian, known for his "down home" style, it took some folks in L.A. a while to adjust to, not only his material, but his diction. One critic left his show utterly confused, saying she couldn't understand him. But that didn't stop others from recognizing and celebrating his brilliance. Spike Lee was the first director to take a chance on Harris by putting him in his classic film, Do The Right Thing. From there his career took off and he was constantly busy, selling out shows across the country. He was expected to blow up even further with all the movie roles, comedy specials and additional exposure. But all of that came to a halt. Harris, who was keeping a busy schedule, also suffered from a breathing problem that often affected his sleep. Just nine days after House Party had been released, Harris who had just finished a show, had dinner with friends, went to a Blues club and later died in his sleep in his hotel room in Chicago.
The film Bebe's Kids, which is a bit from Harris' standup comedy show, was originally going to be a feature with live actors. But in order to pay tribute to Harris, Hudlin decided to continue the project as an animated feature. As a child of the '90's, I'm so glad he did. Bebe's Kids is a classic.
The Sequels
These studios can be so scandalous. Believe it or not, the original director, Hudlin, had nothing to do with the films' sequels. New Line wanted Hudlin to make the movie for the same $2.5 million dollars he made the first one with. Considering the first movie's immense success and the fact that Hudlin was receiving offers from every other major studio, that is quite insulting to say the least. So Hudlin declined. But he's still winning. Since the original idea was his, he's received checks for all of them. No wonder the sequels were pretty crappy after the second one. They lacked the proper direction. Shame.
House Party 5?
Usually, by the time we get to this part, I'm vehemently against touching the classics. And you would think with the current, stinky track record for the House Party 3 and 4, I wouldn't be too excited about this one either…but this one would be directed by Hudlin. Brothers Bowlegged Lou and B-Fine of the rap group and subsequent production company, Full Force, were the guys who played the bullies in the original House Party and recorded the song made popular by the film, "Ain't My Type of Hype." They've stayed in contact with Hudlin over the years and announced earlier this year, at a New York Public Library, that the script for the sequel was being fine tuned. According to Black America Web, Hudlin sees the film coming together as a new school vs. old school party. The Full Force brothers said Kid'n Play are down and Tisha would also join in, if the script is right. I can see potential…what do you think?
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I attended the HR Summit in Barcelona on 12-14 October 2016, which is a long-standing networking event that brings together suppliers and buyers of HR services. Interspersed amongst the meetings, were a series of practitioner-led sessions and I went to a couple of the sessions that talked about culture change.
What interested me is how culture change is talked about in sessions like this. First, a sense of something that's 'done to' rather than 'done by' people - in other words many culture change programmes are in fact doing the very opposite of what they are intended to do: they are disempowering. Second, that the process of change is quite formulaic and simplifies, or at least attempts to simplify, something that is, in practice, emergent and messy. Third, that the leaders and managers of an organisation are somehow blessed with special powers to make the change happen.
Here's what I mean. To start with, you run a series of focus groups to capture how things are working at the moment and how people are feeling. You then identify a set of values and behaviours that describe how the future will look when the culture has been changed and from which you develop a communication and engagement process. In their way, these communications have a kind of pious, almost cult-like, air about them, exhorting the organisation to adopt its new values and behaviours. Into this mix is often the implementation of an expensive leadership development process targeting weary, and somewhat cynical, middle-management to lead the change.
Approaches like this are popular because of the ways in which they first define the problem - there is a starting point - and then create a sense of action that will take us to an end point. Unfortunately, however seductive such approaches are, this is not how change works. They take little or no account of how an organisation actually works in practice: how people talk and interact with each other and how things get done. If a culture can in fact be changed at all, it emerges from what is already being done and has always been done. It can be observed in the many, many taken-for-granted everyday interactions between people.
Releasing what's already there
A few weeks ago, the reading for the day at my local church was the passage from Luke's Gospel (17: 5-6). This describes a change management problem in which Jesus' disciples ask him to increase their faith. Jesus' response is that if you have faith like the grain of a mustard seed, you could make all kinds of extraordinary things happen.
Whatever your personal beliefs, Jesus is saying something here that is very relevant to how we might approach change in organisations. The disciples plea to Jesus is that if you give us more, (in the biblical example it was faith, but we could replace this with skills and behaviours), we can do our work even better. What's interesting is what happens next. Instead of acceding to their request, he turns the question on its head and points out that it's not more faith that's required but to release what is already within themselves.
Where does this lead us?
Whether your mission is to propagate the Gospel or something else, the point is that instead of seeing culture change as being about fixing something, perhaps we are looking at this through the wrong end of the telescope. Maybe what's needed is to find ways that can enable people within an organisation to work together naturally and the product of which enhances what is already present. This means looking for approaches that are practical and that can create a shared experience and ownership. My hunch is what would emerge from this is greater individual self confidence and a clearer sense of what it means to belong in a given working environment.


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Our Mission:
The Jordan Ministry Team includes trained professionals who collaborate with the Diocese of Tucson in response to the Second Vatican Council's universal call to holiness and participation in the mission of the Church. The Team provides theological and spiritual formation to foster Catholic leadership and promote spiritual growth throughout the diocese. Sponsored by the Salvatorian Community, the Jordan Ministry is committed to making Jesus the Savior known and loved by all.
Our Vision:
Inspired by the vision of Father Francis Jordan, the Jordan Ministry Team, composed of members of the Salvatorian community and other religious and lay persons, will promote spiritual and religious formation programs throughout the Catholic Church in Southern Arizona. The focus of its ministry will be spirituality, youth ministry and formation of lay ministers.


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Saturday, 11 June 2011
Sails of White Nights : Only Four Flights of Second Round Robin Remain
Light winds on the Neva river at the start of Sails of White Nights. Image copyright Sails of White Nights.
by Yana Dobzhitskaya
On Friday the regatta " Sails of White Nights » witnessed one more historical event: for the first time in six years of regatta's life the organizers have practically completed the second round-robin.
Struggle for points at the aqua territory went on all day long. Since morning the yachtsmen were pleased with the steady wind whose impulses reached 7 meters per second. As a result the day proved to be rather hot for judges and sportsmen: they have held 10 flights in spite of 28 degree heat. Undue incidents also have taken place. William Tiller yacht's helm has been damaged during a strained fight with the leader of the rating Peter Wibroe.
"It has happened almost right after the start, on the first loop, - the New Zealander tells. - we led the race with a serious advantage, and what's the most annoying – our contender already had got a penalty. So our chances were excellent. But then the rush has come, and we have heard a deaf sound. The yacht suddenly became completely uncontrollable. We have been moved to the middle of the river by the current – directly on the waterway. Fortunately, the emergency boat has arrived at once and has helped us to reach the pontoon where the yacht has been repaired. We didn't run aground, we didn't touch anything, so it is not our fault. But all the same we lost the race – and this vexes us most of all! We have sent our protest to the racing committee and hope that the repeated race will be appointed."
Andrey Arbuzov's crew remains the leader of the race. The skilled yachtsman has lost only twice in 16 races – to the compatriot Sergey Musikhin and Italian Simone Ferrarese. Many contenders mention his ability to work with the current: though the Muscovite participates in the regatta for the sixth year in succession, even this time he visited the water area not in the race time to study all directions of currents. And he used antiquated method: threw the pieces of paper in the water and tried to remember, where and with what speed they were carried away.
- There are no great changes, the current is the same, - Andrew Arbuzov says. - The technique of the turns is more important in this competition. Yesterday, for example, the wind was weaker and it was easier to race for us. And today the wind has blown, and it became more difficult for us to maneuver. So the one who is faster and the one who changes tacks more accurately has better chances to win.
Andrew Arbuzov is followed by several racers: New Zealander William Tiller, who had problems with the helm (11 victories), Sergey Musikhin from Ekaterinburg (10), Finn Staffan Lindberg (10) and Italian Simone Ferrarese (9 victories).
On Saturday the race will start with the remained 4 flights of the second round-robin. After them semi-finals are planned. It's quite pleasant that the weather forecast is fine: the sun and steady wind approximately 5 meters per second are predicted. And for Sunday when the endings are planned, the weather forecast is worse: a wind only about 2 km/s which is too weak for sailing. So for yachtsmen it is important not to lose any start tomorrow, as the winners – in the absence of the wind – will be defined by the results of Saturday races.
Note from SailRaceWin: Full Metal Jacket (Will Tiller, NZL) mentioned that their rudder had snapped in half during one match. This is the incident described above.
Round Robins One (9 matches) + Two (number of matches)
Wibroe (DEN) 3 (9) + 2 (5)
Lindberg (FIN) 6(9) + 3 (4)
Ferrarese (ITA) 7 (9) + 2 (3)
Tiller (NZL) 7 (9) + 3 (5)
Kutovaya (RUS) 1 (9) + 0 (0)
Chapman (AUS) 3 (9) + 1 (5)
Stanczyk (POL) 1 (9) + 2 (6)
Arbuzov (RUS) 8 (9) + 5 (6)
Musikhin (RUS) 6 (9) + 3 (5)
Taranov (RUS) 3 (9) + 2 (7)
Sails of White Nights
at 10:21