high performance computing on graphics processing units: hgpu.org

In this paper, we present our work on developing a new matrix format and a new sparse matrix-vector multiplication algorithm. The matrix format is HEC, which is a hybrid format. This matrix format is efficient for sparse matrix-vector multiplication and is friendly to preconditioner. Numerical experiments show that our sparse matrix-vector multiplication algorithm is efficient […]

Sparse matrix-sparse/dense matrix multiplications, spgemm and csrmm, among other applications find usage in various matrix formulations of graph problems. GPU based supercomputers are presently experiencing severe performance issues on the Graph-500 benchmarks, a new HPC benchmark suite focusing on graph algorithms. Considering the difficulties in executing graph problems and the duality between graphs and matrices, […]

Large, real-world graphs are famously difficult to process efficiently. Not only they have a large memory footprint but most graph processing algorithms entail memory access patterns with poor locality, data-dependent parallelism, and a low compute-to-memory access ratio. Additionally, most real-world graphs have a low diameter and a highly heterogeneous node degree distribution. Partitioning these graphs […]

It is possible to purchase, for as little as $10,000, a cluster of computers with the capability to rival the supercomputers of only a few years ago. Now, users that have little to no experience developing distributed applications or managing a cluster are in a position to do so. To allow domain scientists to effectively […]

For real-time rendering of physically-based volumetric deformation, a meshless finite element method (FEM) is proposed and implemented on the new-generation Graphics Processing Unit (GPU). A tightly coupled deformation and rendering pipeline is defined for seamless modeling and rendering: First, the meshless FEM model exploits the vertex shader stage and the transform feedback mechanism of the […]

The common approach to program many-core processor is to write processor-specific code with low level APIs for different processors, which could achieve good performance but would result in serious portability issues: programmers are required to write a specific version code for target architecture. Therefore, we present ab-Stream, an extensible framework for programming many-threaded processor based […]

This paper presents results of an implementation of code generator for fast general matrix multiply (GEMM) kernels. When a set of parameters is given, the code generator produces the corresponding GEMM kernel written in OpenCL. The produced kernels are optimized for high-performance implementation on GPUs from AMD. Access latencies to GPU global memory is the […]

This paper presents a framework that extends OpenCL by distributing computing process to many computing resources connected via network and enables the computing resources to run in parallel. Using JSON RPC (Remote Procedure Call technique relying on JavaScript Object Notation) in communication layer, Distributed OpenCL framework provides platform and operating system independency. Using this framework, […]

Graphics engines are excellent execution platforms for high-throughput computations that exploit a large degree of available parallelism. The achieved performance is, however, highly dependent on the access patterns that the application imposes on the memory subsystem. Here, we propose an analytic model that helps improve the understanding of the performance of memory-limited kernels that employ […]

High Performance Computing (HPC) is rapidly becoming an integral part of Science,Engineering and Business. Scientists and engineers are leveraging HPC solutions to run their applications that require high bandwidth, low latency, and very high compute capabilities. General Purpose Graphics Processing Units (GPGPUs)are becoming more popular within the HPC community because of their highly parallel structure, […]

This thesis describes typical spectral imaging techniques and spectral image analysis algorithms that are in general use. Three developed spectral imaging systems are proposed. The first imaging system consists of two line scanning based spectral cameras. These cameras are combined in one simultaneous measuring process, which can be used for capturing a wide range of […]

We consider the recovery of sparse signals from a limited number of noisy observations using the AMP algorithm. In this paper, we present two fast implementations of this algorithm that run on a CPU and on a GPU and which can either be used for arbitrary unstructured measurement matrices or take advantage of the structure […]