OpenCL CodeBench is a code creation and productivity tools suite designed to accelerate and simplify OpenCL software development. OpenCL CodeBench provides developers with automation tools for host code and unit test bench generation. Kernel code development on OpenCL is accelerated and enhanced through a language aware editor delivering advanced incremental code analysis features. Software Programmers new to OpenCL can choose to be guided through an Eclipse wizard, while the power users can leverage the command line interface with XML-based configuration files. OpenCL CodeBench Beta is now available for Linux and Windows operating systems.
Jacket enables GPU computing for MATLAB® codes. The new version v2.3 includes performance improvements and new support for CUDA 5.0. This newer version of CUDA enables computation on the latest Kepler K20 GPUs of the NVIDIA Tesla product line.
More information: http://blog.accelereyes.com/blog/2012/10/23/jacket-v2-3/
The CUDA 5 Production Release is now available as a free download at www.nvidia.com/getcuda.
This powerful new version of the pervasive CUDA parallel computing platform and programming model can be used to accelerate more of applications using the following four (and many more) new features.
• CUDA Dynamic Parallelism brings GPU acceleration to new algorithms by enabling GPU threads to directly launch CUDA kernels and call GPU libraries.
• A new device code linker enables developers to link external GPU code and build libraries of GPU functions.
• NVIDIA Nsight Eclipse Edition enables you to develop, debug and optimize CUDA code all in one IDE for Linux and Mac OS.
• GPUDirect Support for RDMA provides direct communication between GPUs in different cluster nodes
As a demonstration of the power of Dynamic Parallelism and device code linking, CUDA 5 includes a device-callable version of the CUBLAS linear algebra library, so threads already running on the GPU can invoke CUBLAS functions on the GPU. Read the rest of this entry »
AMD CodeXL is a new unified developer tool suite that enables developers to harness the benefits of CPUs, GPUs and APUs. It includes powerful GPU debugging, comprehensive GPU and CPU profiling, and static OpenCL™ kernel analysis capabilities, enhancing accessibility for software developers to enter the era of heterogeneous computing. AMD CodeXL is available for free, both as a Visual Studio® extension and a standalone user interface application for Windows® and Linux®.
AMD CodeXL increases developer productivity by helping them identify programming errors and performance issues in their application quickly and easily. Now developers can debug, profile and analyze their applications with a full system-wide view on AMD APU, GPU and CPUs.
AMD CodeXL user group (requires registration) allows users to interact with the CodeXL team, provide feedback, get support and participate in the beta surveys.
The OpenFOAM CFD Toolbox is a free, open source CFD software package produced by OpenCFD Ltd. Its user base represents a wide range of engineering and science disciplines in both commercial and academic organizations. OpenFOAM has an extensive range of features to solve a wide range of fluid flows and physics phenomenon. OpenFOAM provides tools for all three stages of CFD, preprocessing, solvers, and post processing. Almost all are capable of being run in parallel as standard making it an important resource for a wide range of scientists and engineers using HPC for CFD.
General-purpose Graphics Processing Unit (GPU) technology is increasingly being used to accelerate compute-intensive HPC applications across various disciplines in the HPC community. OpenFOAM CFD simulations can take a significant amount of time and are computationally intensive. Comparing various alternatives for enabling faster research and discovery using CFD is of key importance. SpeedIT libraries from Vratis provide GPU-accelerated iterative solvers that replace the iterative solvers in OpenFOAM.
In order to investigate the GPU-acceleration of OpenFOAM, we simulate the three dimensional lid-driven cavity problem based on the tutorial provided with OpenFOAM. The 3D lid-driven cavity problem is an incompressible flow problem solved using OpenFOAM icoFoam solver. The majority of the computationally intensive portion of the solver is the pressure equation. In the case of acceleration, only the pressure calculation is offloaded to the GPUs. On the CPUs, the PCG solver with DIC preconditioner is used. In the GPU-accelerated case, the SpeedIT 2.1 algebraic multigrid precoditioner with smoothed aggregation (AMG) in combination with the SpeedIT Plugin to OpenFOAM is used.
Recognizing the growing interest and demand from NSF researchers for education on GPU computing, leading centers in NSF’s Extreme Science and Engineering Discovery Environment (XSEDE) program are working together to host a free two-day, hands-on workshop to share tips and best practices for accelerating scientific applications on GPUs using OpenACC. More information: http://blogs.nvidia.com/2012/09/u-s-scientists-nsf-to-host-nationwide-gpu-computing-workshop/
The Vrije Universiteit Brussel, Erasmus Hogeschool Brussel and Lessius Hogeschool have the pleasure to invite you to a symposium on Personal High-Performance Computing. The symposium aims at bringing together academia and industry to discuss recent advances in using accelerators such as GPUs or FPGAs for speeding up computational-intensive applications. We target single systems such as PCs, laptops or processor boards, hence the name ‘personal’ HPC.
Scientists are encouraged to submit abstracts to be presented at the poster session. All information can be found at https://sites.google.com/site/phpc2012bxl.
The Computing Language Utility (CLU) is a lightweight API designed to help programmers explore, learn, and rapidly prototype programs with OpenCL. This API reduces the complexity associated with initializing OpenCL devices, contexts, kernels and parameters, etc. while preserving the ability to drop down to the lower level OpenCL API at will when programmers wants to get their hands dirty. The CLU release includes an open source implementation along with documentation and samples that demonstrate how to use CLU in real applications. It has been tested on Windows 7 with Visual Studio.
The MOSIX group announces the release of the Virtual OpenCL (VCL) cluster platform version 1.14. This version includes the SuperCL extension that allows micro OpenCL programs to run efficiently on devices of remote nodes. VCL provides an OpenCL platform in which all the cluster devices are seen as if they are located in the hosting-node. This platform benefits OpenCL applications that can use many devices concurrently. Applications written for VCL benefit from the reduced programming complexity of a single computer, the availability of shared-memory, multi-threads and lower granularity parallelism, as well as concurrent access to devices in many nodes. With SuperCL, a programmable sequence of kernels and/or memory operations can be sent to remote devices in cluster nodes, usually with just a single network round-trip. SuperCL also offers asynchronous communication with the host, to avoid the round-trip waiting time, as well as direct access to distributed file-systems. The VCL package can be downloaded from mosix.org.
Graphics Core Next Architecture Overview
GCN is Designed to push not only the boundaries of DirectX® 11 gaming, the GCN Architecture is also AMD’s first design specifically engineered for general computing. Equipped with up to 32 compute units (2048 stream processors), each containing a scalar coprocessor, AMD’s 28nm GPUs are more than capable of handling workloads-and programming languages-traditionally exclusive to the processor. Coupled with the dramatic rise of GPU-aware programming languages like C++ AMP and OpenCL™, the GCN Architecture is truly the right architecture for the right time. Participate in this webinar to learn how you can take advantage of this new architecture in your GPGPU programs (North America – August 14, 2012 10AM Pacific Daylight savings Time; India- August 21, 2012, 5:30PM India Standard Time).
Performance Evaluation of AMD APARAPI Using Real World Applications