high performance computing on graphics processing units: hgpu.org

This project focuses on using GPGPUs for solving the inexact alignment of short-reads with respect to a reference indexed using the Burrows-Wheeler Transform. To be more specific we dealt with a solution of an alignment that allows up to one error.

Along with the inclusion of GPU cores within the same CPU die, the performance of Intel’s processor-graphics has been significantly improved over earlier generation of integrated graphics. The need to efficiently harness the computational power of the GPU in the same CPU die is more than ever. This paper presents a highly optimized Haar-based face […]

Motion estimation is the key part of video compression since it removes the temporal redundancy within frames and significantly affects the encoding quality and efficiency. In this paper, a novel fast motion estimation algorithm named Clustering Based Search algorithm is proposed, which is the first to define the clustering feature of motion vectors in a […]

With accurate simulation of ever-more complex phenomena desired, numerical models are getting increasingly sophisticated and thus take considerable amount of time to run on normal computers. Parallel computing has emerged as an important paradigm in response, allowing engineers to run programs faster. In recent years graphics processing units (GPU) are among the massively parallel devices […]

BACKGROUND and PURPOSE: The objective of brain perfusion quantification is to generate parametric maps of relevant hemodynamic quantities such as cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) that can be used in diagnosis of acute stroke. These calculations involve deconvolution operations that can be very computationally expensive when using […]

The purpose of this paper is to propose effective parallelization strategies for the Iterated Local Search (ILS) metaheuristic on Graphics Processing Units (GPU). We consider the decomposition of the 3-opt Local Search procedure on the GPU processing hardware and memory structure. Two resulting algorithms are evaluated and compared on both speedup and solution quality on […]

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 […]