high performance computing on graphics processing units: hgpu.org

The Conjugate Gradient (CG) method is a widely-used iterative method for solving linear systems described by a (sparse) matrix. The method requires a large amount of Sparse-Matrix Vector (SpMV) multiplications, vector reductions and other vector operations to be performed. We present a number of mappings for the SpMV operation on modern programmable GPUs using the […]

String matching is a classical problem in computer science. After the study of the Naive string search, Brute Force and the KMP algorithm, several advantages and disadvantages of the algorithms have been analyzed. Considering KMP in particular concept of parallelization has been introduced to improve the performance of the KMP algorithm. The algorithm is designed […]

In this paper, we present the parallelization design consideration for irregular algorithms of video processing on GPUs. Enrich parallelism can be exploited by scheduling the processing order or making a tradeoff between performance and parallelism for irregular algorithms (such as CAVLC and deblocking filter). We implement a component-oriented CAVLC encoder and a direction-oriented deblocking filter […]

We have ported an implementation of the spin-up for marine ecosystem models based on the "Transport Matrix Method" to graphics processing units (GPUs). The original implementation was designed for distributed-memory architectures and uses the PETSc library that is based on the "Message Passing Interface (MPI)" standard. The spin-up computes a steady seasonal cycle of the […]

In this paper, we present two new parallel algorithms to solve large instances of the scheduling of independent tasks problem. First, we describe a parallel version of the Min-min heuristic. Second, we present GraphCell, an advanced parallel cellular genetic algorithm (CGA) for the GPU. Two new generic recombination operators that take advantage of the massive […]

In recent years, GPU-CPU heterogeneous architectures have been increasingly adopted in high performance computing, because of their capabilities of providing high computational throughput. However, current research focuses mainly on the performance aspects of GPU-CPU architectures, while improving the energy efficiency of such systems receives much less attention. There are few existing efforts that try to […]

We develop GPU adaptations of the Aho-Corasick and multipattern Boyer-Moore string matching algorithms for the two cases GPU-to-GPU (input is initially in GPU memory and the output is left in GPU memory) and host-to-host (input and output are in the memory of the host CPU). For the GPU-to-GPU case, we consider several refinements to a […]

In this paper, we propose a new parallel statistical analysis method for large analog circuits using determinant decision diagram (DDD) based graph technique based on GPU platforms. DDD-based symbolic analysis technique enables exact symbolic analysis of vary large analog circuits. But we show that DDD-based graph analysis is very amenable for massively threaded based parallel […]

With the rising number of application accelerators, developers are looking for ways to evaluate new and competing platforms quickly, fairly, and early in the development cycle. As high-performance computing (HPC) applications increase their demands on application acceleration platforms, graphics processing units (GPUs) provide a potential solution for many developers looking for increased performance. Device performance […]

As one of the important tasks in digital terrain analysis, the calculation of flow accumulations from gridded digital elevation models (DEMs) usually involves two steps in a real application: (1) using an iterative DEM preprocessing algorithm to remove the depressions and flat areas commonly contained in real DEMs, and (2) using a recursive flow-direction algorithm […]

With the introduction of GPGPUs, parallel programming has become simple and affordable. APIs such as NVIDIA’s CUDA have attracted many programmers to port their applications to GPGPUs. But writing CUDA codes still remains a challenging task. Moreover, the vast repositories of legacy serial C codes, which are still in wide use in the industry, are […]

Over the last decades Cellular Automata (CA) have become more and more present in solving general-purpose problems, but the main issue is how to map a problem to a Cellular Automata model. Special languages were developed for programming such models, but learning a new programming language is very time consuming. Furthermore software developers have to […]