December 2011 saw the kick-off of an ambitious research project called “CARP: Correct and Efficient Accelerator Programming”, which aims to boost the programmability of accelerator hardware, such as graphics processing units (GPUs), by innovating in programming language design and implementation, as well as formal verification techniques. Funded by the European Commission’s Seventh Framework Programme (FP7), the consortium, which consists of eight partners--including Khronos members ARM, Imperial College London and Rightware--seeks to provide a unified flow for developing correct and efficient accelerator software, thus increasing reliability and energy efficiency of computing systems.
The AMD OpenCL APP SDK v2.7 now supports OpenCL 1.2 and improved C++ support for both host side and kernel side coding.
Vivante Corporation today announced Vivante GC Cores passed the Khronos Group OpenCL 1.1 Embedded Profile (EP) conformance test suite on Freescale's i.MX 6 platform. The GC Cores use the latest programmable ScalarMorphic architecture to accelerate parallel data workloads on thousands of concurrent threads to achieve Gigaflops (GFLOPS) of computational performance. Applications taking advantage of Vivante cores to significantly speed-up processing includes image processing, computer vision, analytics, augmented reality and gesture-motion tracking.
Imagination was showing off GPU compute on a cell phone chip at GDC, physics in your pocket. That demo was pretty simple, take a Pandaboard with a TI OMAP 4430, a dual-core ARM A9 CPU and an Imagination SGX540 GPU, and run a cloth simulation on it. Not only could the OpenCL version exploit the GPU to do more balls and sheets than the CPU version, but it saved power while doing so. How much? On one CPU, the simulation took about .68A@5V to run at 14FPS with 100% CPU load. With two A9 cores loaded, the Pandaboard pulled .84A and ran at 24FPS. In OpenCL, CPU load dropped to less than 30%, FPS jumped to 42, and power draw went down to .60A. More than 10% less energy used, 3x the frame rate, and you could run more simulations on the same box if you wanted. Not bad at all.
Marketing Manager for Intel HD Graphics demos several examples of how the Intel SDK for OpenCL Applications 2012 supports 3rd generation Intel Core processors on both Intel Processors and HD graphics 4000/2500 for accelerated video processing.
This book contains the most important and essential information required for designing correct and efficient OpenCL programs. Some details have been omitted but can be found in the provided references. The authors assume that readers are familiar with basic concepts of parallel computation, have some programming experience with C or C++ and have a fundamental understanding of computer architecture. In the book, all terms, definitions and function signatures have been copied from official API documents available on the page of the OpenCL standards creators.
The book starts with the basics of parallelization, covers the main concepts, grammar, and setting up a development environment for OpenCL, concluding with source-code walkthroughs of the FFT and Mersenne Twister algorithms written in OpenCL. The revised edition includes a summary of changes made in OpenCL Specification 1.2, reference functions corresponding to 1.2, and updated excursion environments. It is highly recommended for those wishing to get started on programming in OpenCL.
NVIDIA announces the dual-chip GeForce GTX 690, powered by two Kepler-generation GK104 graphics processors. With the help of 3072 stream processors, the device is set to establish new performance records. The card supportsOpenGL 4.2, OpenCL 1.2 and DirectX 11.1.
Kishonti Informatics has launched the community version of CLBenchmark 1.1 Desktop Edition. CLBenchmark provides a free and easy-to-use tool for consumers and media professionals to compare the processing power of different hardware architectures.