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Confessions of a Speed Junkie (Products)

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Confessions of a Speed Junkie (Products) | gpgpu-computing1.blogspot.com Reviews

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Confessions of a Speed Junkie (Products): AccelerEyes (Jacket)

http://gpgpu-computing1.blogspot.com/2009/08/accelereyes-jacket.html

Confessions of a Speed Junkie (Products). Monday, August 10, 2009. AccelerEyes' first product, Jacket, is used by customers across all major HPC industries, such as the automotive, financial, medical, and seismic industries. Further, Jacket's Graphics Toolbox enables true Visual Computing, seamlessly merging the compute power of CUDA with OpenGL visualizations. AccelerEyes plans to adapt and expand Jacket for other hardware and software platforms. Jacket is not another GPU API, nor is it simply a collect...

2

Confessions of a Speed Junkie (Products): RapidMind

http://gpgpu-computing1.blogspot.com/2009/08/rapidmind.html

Confessions of a Speed Junkie (Products). Monday, August 10, 2009. Multi-core processors offer tremendous performance gains, but few applications take full advantage of this new technology because of the significant complexity of parallelizing across the multiple cores. Applications that are not multi-core enabled will suffer a performance decrease as it will only run on a single core, and will not scale as the number of cores increases. Multi-core processing presents an opportunity for software organiza...

3

Confessions of a Speed Junkie (Products): Advanced Derivatives Solutions (Q-GPU)

http://gpgpu-computing1.blogspot.com/2009/08/advanced-derivatives-solutions-q-gpu.html

Confessions of a Speed Junkie (Products). Monday, August 10, 2009. Advanced Derivatives Solutions (Q-GPU). Q-GPU (Quantara-GPU) is a high performance options analytics for pricing and risk managing exotic structures. Q-GPU is based on the NVIDIA-Cuda high performance computing technology to price a wide range of interest rate structures using state-of-the-art stochastic volatility and multi-factor models. For more information http:/ www.aderivatives.com/index.html. Posted by Dr Zaius. 2) Tesla S1070 1U.

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Confessions of a Speed Junkie (Products): The Portland Group

http://gpgpu-computing1.blogspot.com/2009/08/portland-group.html

Confessions of a Speed Junkie (Products). Monday, August 10, 2009. The focus of the Portland Group is to provide the highest performance, production quality compilers and software development tools to the High Performance Technical Computing (HPTC) market. You will find below a short overview of The Portland Group and the PGI product strategy and products. For more information http:/ www.pgroup.com/. Posted by Dr Zaius. Monday, August 10, 2009. 3) Advanced Derivative Solutions. 1) The Portland Group.

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Confessions of a Speed Junkie (Products): Hanweck Associates (Volera)

http://gpgpu-computing1.blogspot.com/2009/08/hanweck-associates-volera.html

Confessions of a Speed Junkie (Products). Monday, August 10, 2009. Hanweck Associates, LLC is a premier financial services provider specializing in risk management solutions for top-tier hedge funds, banks, broker/dealers and other financial institutions. Hanweck Associates is an established leader in high-performance financial computing. We pioneered commercial GPU-based computing solutions for the financial industry with products such as Volera, our low-latency, real-time options analytics engine.

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Confessions of a Speed Junkie (Resources): CUDA Zone

http://gpgpu-computing2.blogspot.com/2009/08/cuda-zone.html

Confessions of a Speed Junkie (Resources). Tuesday, August 11, 2009. Nvidia has put together a webportal for CUDA developers called the CUDA Zone. This site contains documentation, software, examples of what others are doing with CUDA, tutorials, and the official CUDA forums. Http:/ www.nvidia.com/object/cuda home.html#. Posted by Dr Zaius. Tuesday, August 11, 2009. 5) Sign up for CUDA Alerts. 4) AMD OpenCL Forums.

gpgpu-computing4.blogspot.com gpgpu-computing4.blogspot.com

Confessions of a Speed Junkie (Code Examples): Matrix Multiplication 2 (OpenCL)

http://gpgpu-computing4.blogspot.com/2009/09/matrix-multiplication-2-opencl.html

Confessions of a Speed Junkie (Code Examples). Monday, September 28, 2009. Matrix Multiplication 2 (OpenCL). I will assume that you have gone through the CUDA Matrix Multiplication 2. Example and understand the conceptual changes that we will be making to our OpenCL kernel. All we really need to do is express our kernel from CUDA Matrix Multiplication 2 in terms of OpenCL and slightly modify our main program from our OpenCL Matrix Multiplication 1. Main program (Listing 1). Multiply two matrices A * B = C.

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Confessions of a Speed Junkie (Code Examples): CUDA Program Structure

http://gpgpu-computing4.blogspot.com/2009/08/cuda-program-structure.html

Confessions of a Speed Junkie (Code Examples). Tuesday, August 25, 2009. CUDA’s parallel programming model is designed to overcome the many challenges of parallel programming while providing a quick learning curve for programmers familiar with C. At its core are three abstractions: a hierarchy of thread groups, shared memory, and thread synchronization. These abstractions are exposed to the programmer via a small set of language extensions. C for CUDA provides a minimal set of extensions to the C languag...

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Confessions of a Speed Junkie (Overview): Change... It's a good thing

http://gpgpu-computing.blogspot.com/2009/08/change-its-good-thing.html

Confessions of a Speed Junkie (Overview). Friday, August 14, 2009. Change. It's a good thing. So now you know what GPGPU is, what it is not, the magnitude of the performance gains you can expect to get now and in the near future, and a bit of history as to how we got here. But how can you effect the necessary change in your organization to benefit from this new technology? With all of these impediments to change how do you get the ball rolling? Section and subscribe to my site feed. Live Free or Die.

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Confessions of a Speed Junkie (Code Examples): Matrix Multiplication 1 (CUDA)

http://gpgpu-computing4.blogspot.com/2009/08/matrix-multiplication-1.html

Confessions of a Speed Junkie (Code Examples). Thursday, August 27, 2009. Matrix Multiplication 1 (CUDA). I will assume that you have already downloaded and installed the appropriate CUDA driver, toolkit and SDK from Nvidia. I am using version 2.2 but what we are covering should work with any version. If you don’t already have the software and driver installed go to http:/ www.nvidia.com/object/cuda get.html. Main program (Listing 1). Multiply two matrices A * B = C. Void randomInit(float* data, int size).

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Confessions of a Speed Junkie (Resources): OpenCL Tutorials

http://gpgpu-computing2.blogspot.com/2009/08/opencl-tutorials.html

Confessions of a Speed Junkie (Resources). Thursday, August 13, 2009. AMD has put together a very basic OpenCL tutorial using the proposed C bindings to OpenCL. This tutorial can be found at. Http:/ developer.amd.com/gpu/ATIStreamSDK/pages/TutorialOpenCL.aspx. AMD is working with Mindshare to develope a 3 day class on OpenCL programming. The class is not yet available but should be soon. For more information. Http:/ www.mindshare.com/learn/? Posted by Dr Zaius. Thursday, August 13, 2009.

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Confessions of a Speed Junkie (Code Examples): OpenCL Program Structure

http://gpgpu-computing4.blogspot.com/2009/09/opencl-program-structure.html

Confessions of a Speed Junkie (Code Examples). Thursday, September 17, 2009. As of today there have been no OpenCL implementations released. AMD and Nvidia are both working on implementations for their processors but they are both still in beta. All of the following examples have been built and tested against Nvidia’s beta OpenCL. So how much more complicated is OpenCL? With OpenCL we have an NDRange (N – Dimensional Range) of work groups that contain multiple work items. Posted by Dr Zaius.

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Confessions of a Speed Junkie (Resources): OpenCL Documentation

http://gpgpu-computing2.blogspot.com/2009/08/opencl-documentation.html

Confessions of a Speed Junkie (Resources). Thursday, August 13, 2009. The OpenCL specification is maintained by the Khronos group. It can be found at. Http:/ www.khronos.org/registry/cl/specs/opencl-1.0.43.pdf. The SIGGRAPH ASIA Khronos OpenCL presentation by Neil Trevett of NVIDIA can be found at. Http:/ www.khronos.org/developers/library/overview/opencl overview.pdf. There is a quick reference card for OpenCL 1.0 API that can be found at. Http:/ sites.amd.com/us/fusion/apu/Pages/fusion.aspx.

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Confessions of a Speed Junkie (News): AccelerEyes Supports Fermi

http://gpgpu-computing3.blogspot.com/2010/07/accelereyes-supports-fermi.html

Confessions of a Speed Junkie (News). Thursday, July 15, 2010. AccelerEyes develops Jacket, a software platform that delivers GPU computing power to desktop users of MATLAB and other very high level languages. It enables faster prototyping and problem solving across a range of government, manufacturing, energy, media, biomedical, financial, and scientific research applications. The Jacket software platform enables accelerated double-precision performance for common arithmetic and linear algebra f...

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Confessions of a Speed Junkie (News): December 2009

http://gpgpu-computing3.blogspot.com/2009_12_01_archive.html

Confessions of a Speed Junkie (News). Wednesday, December 16, 2009. David takes on Goliath…. 8230; and, while the battle still rages on, David appears to be winning. Fast forward to December 2009 and you will find no mention of AMDs Falcon and Swift. However, AMD does not appear to have thrown in the towel yet. They are still working on Fusion and claim they will have something out in 2010. Posted by Dr Zaius. Wednesday, December 16, 2009. Thursday, December 10, 2009. State of the GPGP Union. I’ve ...

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Confessions of a Speed Junkie (Overview)

Confessions of a Speed Junkie (Overview). Friday, August 14, 2009. In the past if a programs performance was less than adequate for the user you could typically just buy more powerful hardware to make it faster. With the impending collapse of Moore's law this will no longer be true. So until they come up with subatomic computing, programmers will need to embrace parallel computing more in order to squeeze performance gains from their applications. So why am I posting this? Because GPGPU is, in my opinion...

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Confessions of a Speed Junkie (Products)

Confessions of a Speed Junkie (Products). Tuesday, August 18, 2009. CULA is a LAPACK library from EM Photonics. It comes in three flavors: basic, premium, and commercial. For more information http:/ www.culatools.com/. Posted by Dr Zaius. Tuesday, August 18, 2009. Tuesday, August 11, 2009. For more information http:/ www.supermicro.com/products/nfo/gpu.cfm. Posted by Dr Zaius. Tuesday, August 11, 2009. You can build your own GPU cluster with Nvidia S1070 1Us connected to rack mounted servers. You wil...

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Confessions of a Speed Junkie (Resources)

Confessions of a Speed Junkie (Resources). Thursday, August 13, 2009. Nvidia has an OpenCL beta download available. Nvidia's OpenCL driver will only allow you to run on Nvidia devices. You must register as a Nvidia developer to gain access. For more information. Http:/ www.nvidia.com/object/cuda opencl.html. Http:/ developer.amd.com/gpu/ATIStreamSDKBetaProgram/Pages/default.aspx. Posted by Dr Zaius. Thursday, August 13, 2009. Http:/ developer.amd.com/gpu/ATIStreamSDK/pages/TutorialOpenCL.aspx. Nvidia web...

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Confessions of a Speed Junkie (News)

Confessions of a Speed Junkie (News). Thursday, July 15, 2010. EM Photonics Supports Fermi. EM Photonics, Inc. announced today the general availability of CULA 2.0, its GPU-accelerated linear algebra library used by thousands of developers and scientists worldwide. The new version provides support for NVIDIA GPUs based on the latest "Fermi" architecture, which offers HPC users unprecedented performance in double-precision mathematics, faster memory, and new usability features. Posted by Dr Zaius. Acceler...

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Confessions of a Speed Junkie (Code Examples)

Confessions of a Speed Junkie (Code Examples). Friday, October 2, 2009. Matrix Multiplication 3 (OpenCL). The memory model for OpenCL applications is strikingly similar to the CUDA memory model (go figure). The only real differences are that CUDA supports texture memory (we didn't get into that in our CUDA examples) and OpenCL provides for a global / constant memory cache (Nvidias new Fermi GPU. Adds a global / constant memory cache). Global Memory (CUDA Global). Constant Memory (CUDA Constant). While it...

gpgpu-computing5.blogspot.com gpgpu-computing5.blogspot.com

Confessions of a Speed Junkie (Benchmarks)

Confessions of a Speed Junkie (Benchmarks). Friday, August 14, 2009. Binomial Option Model Metrics. The GPU that I am using is an Nvidia C1060 Tesla card. The card is housed in a Dell 690 with a 3.2 GHz Intel Xeon processor, 2G of RAM, and the C1060 installed. The system is running RedHat 5.3 64 bit with Nvidia's 3.0 Beta SDK and appropriate beta driver installed. As you can see from the graph above the fastest version of the model was the CUDA implementation. The CUDA version of the model was 2....What ...

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