high performance computing on graphics processing units: hgpu.org

GPUs as general purpose processors already are well adopted in scientific and high performance computing. Their steadily increasing success caused others than GPU hardware vendors to work on many{core processors as hardware accelerators. With CUDA and OpenCL there are two frameworks available for GPU programming. Apart from potential compatibility problems with the upcoming hardware, both […]

SPIRE is a new, generic, parallel extension for the intermediate representations used in compilation frameworks of sequential languages; it intends to easily leverage their existing infrastructure to address both control and data parallel languages. Since the efficiency and power of the transformations and optimizations performed by compilers are closely related to the presence of a […]

Programming parallel machines as effectively as sequential ones would ideally require a language that provides high-level programming constructs in order to avoid the programming errors frequent when expressing parallelism. Since task parallelism is often considered more error-prone than data parallelism, we survey six popular and efficient parallel programming languages that tackle this difficult issue: Cilk, […]

We have developed CPU and GPU versions of an automated image analysis and classification system for protein crystallization trial images from the Hauptman Woodward Institute’s High-Throughput Screening lab. The analysis step computes 12,375 numerical features per image. Using these features, we have trained a classifier that distinguishes 11 different crystallization outcomes, recognizing 80% of all […]

The recent use of graphics processing units (GPUs) in several top supercomputers demonstrate their ability to consistently deliver positive results in high-performance computing (HPC). GPU support for significant amounts of parallelism would seem to make them strong candidates for non-HPC applications as well. Server workloads are inherently parallel; however, at first glance they may not […]

Highly parallel computing architectures such as graphics processing units (GPUs) pose several new challenges for scientific computing, which have been absent on single core CPUs. However, a transition from existing serial code to parallel code for GPUs often requires a considerable amount of effort. The Vienna Computing Library (ViennaCL) presented in the beginning of this […]

The use of accelerators such as graphics processing units (GPUs) has become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high-performance computers, machines with nodes containing more than one type of floating-point processor (e.g. CPU and GPU), are now becoming more […]

Graphics Processor Units (GPUs) are known for offering high performance and power efficiency for processing algorithms that suit well to their massively parallel architecture. Unfortunately, as parallel programming for this kind of architecture requires a complex distribution of tasks and data, developers find it difficult to implement their applications effectively. Although approaches based on source-to-source […]

Outlier detection (also known as anomaly detection) is a common data mining task in which data points that lie outside expected patterns in a given dataset are identified. This is useful in areas such as fault detection, intrusion detection and in pre-processing before further analysis. There are many approaches already in use for outlier detection, […]

Recently, in many important domains, high-level languages have become the code representations with widest platform support surpassing any low-level language in their area with respect to completeness and importance as exchange format (e.g. OpenCL for data-parallel computing, GLSL/HLSL for shader programs, JavaScript for the web). The code representations of many actively-developed compiler frameworks [JVM,LLVM,FIRM] are […]

Modern Graphical Processing Units (GPUs) can perform general purpose computing, next to standard graphical processing. Open frameworks, such as the OpenCL standard by the Khronos Group, enable developers to easily harness the computational power of GPUs. While in certain aspects, these are more powerful than standard CPUs, the latter are still a more suitable solution […]

SkePU is a C++ template library that provides a simple and unified interface for specifying data-parallel computations with the help of skeletons on GPUs using CUDA and OpenCL. The interface is also general enough to support other architectures, and SkePU implements both a sequential CPU and a parallel OpenMP backend. It also supports multi-GPU systems. […]