EEDSP

This site contains Java bindings for CUDA, CUBLAS, CUFFT, CUDPP, CURAND and CUSPARSE

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.

The CUDA 5 Production Release is now available as a free download at www.nvidia.com/getcuda.

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

SnuCL is an OpenCL framework and freely available, open-source software developed at Seoul National University. It naturally extends the original OpenCL semantics to the heterogeneous cluster environment.

In this work, we describe a simple and powerful method to implement real-time multi-agent path-finding on Graphics Processor Units (GPUs). The technique aims to find potential paths for many thousands of agents, using the A* algorithm and an input grid map partitioned into blocks. We propose an implementation for the GPU that uses a search space decomposition approach to break down the forward search A* algorithm into parallel independently forward sub-searches. We show that this approach fits well with the programming model of GPUs, enabling planning for many thousands of agents in parallel in real-time applications such as computer games and robotics. The paper describes this implementation using the Compute Unified Device Architecture programming environment, and demonstrates its advantages in GPU performance compared to GPU implementation of Real-Time Adaptive A*.

GacUI is a GPU accelerated user interface library for C++ programming language. It provides similar features as WPF, but some features is limited by C++, such as dependency properties. Here are main features:

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®.

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.

In this paper, we show how to employ Graphics Processing Units (GPUs) to provide an efficient and high performance solution for finding frequent items in data streams. We discuss several design alternatives and present an implementation that exploits the great capability of graphics processors in parallel sorting. We provide an exhaustive evaluation of performances, quality results and several design trade-offs. On an off-the-shelf GPU, the fastest of our implementations can process over 200 million items per second, which is better than the best known solution based on Field Programmable Gate Arrays (FPGAs) and CPUs. Moreover, in previous approaches, performances are directly related to the skewness of the input data distribution, while in our approach, the high throughput is independent from this factor.