high performance computing on graphics processing units: hgpu.org

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The Intel Xeon Phi coprocessor is a new choice for the high performance computing industry and it needs to be tested. In this thesis, we compared the difference in performance between the Xeon Phi and the GPU. The Smith-Waterman algorithm is a widely used algorithm for solving the sequence alignment problem. We implemented two versions […]

In this paper, we present parallel programming approaches to calculate the values of the cells in matrix’s scoring used in the Smith-Waterman’s algorithm for sequence alignment. This algorithm, well known in bioinformatics for its applications, is unfortunately time-consuming on a serial computer. We use formulation based on anti-diagonals structure of data. This representation focuses on […]

The complexity of the design of radio networks has grown with the adoption of modern standards. Therefore, the role of the computer for the faster delivery of accurate results has become increasingly important. In this thesis, novel methods for the planning and automatic optimization of radio networks are developed and discussed. The state-of-the-art metaheuristic algorithms, […]

This paper presents a spectral element finite element scheme that efficiently solves elliptic problems on unstructured hexahedral meshes. The discrete equations are solved using a matrix-free preconditioned conjugate gradient algorithm. An additive Schwartz two-scale preconditioner is employed that allows h-independence convergence. An extensible multi-threading programming API is used as a common kernel language that allows […]

Many scientific and numerical applications, including quantum chemistry modeling and fluid dynamics simulation, require tensor product and tensor contraction evaluation. Tensor computations are characterized by arrays with numerous dimensions, inherent parallelism, moderate data reuse and many degrees of freedom in the order in which to perform the computation. The best-performing implementation is heavily dependent on […]

We describe a framework for generating optimized GPU code for computing tensor contractions, a multidimensional generalization of matrix-matrix multiplication that arises frequently in computational science applications. Typical performance optimization strategies for such computations transform the tensors into sequences of matrix-matrix multiplications to take advantage of an optimized BLAS library, but this approach is not appropriate […]

With the advent of parallel processing architectures and a steep increase in parallelism found among the recent applications, GPGPUs have gained attention with respect to their importance in the execution of these applications. In this document, we specifically analyze Sparse-Matrix Vector Multiplication(SPMV) across different architectures, libraries and matrix formats. The experimental platforms include but are […]

RSA is one the most well-known public-key cryptosystems widely used for secure data transfer. An RSA encryption key includes a modulus n which is the product of two large prime numbers p and q. If an RSA modulus n can be decomposed into p and q, the corresponding decryption key can be computed easily from […]

Bidirectional Texture Function (BTF) as an effective visual fidelity representation of surface appearance is becoming more and more widely used. In this paper we report on contributions to BTF data compression for multi-level vector quantization. We describe novel decompositions that improve the compression ratio by 15% in comparison with the original method, without loss of […]