high performance computing on graphics processing units: hgpu.org

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Verifying GPU Kernels by Test Amplification

Alan Leung, Manish Gupta, Yuvraj Agarwal, Rajesh Gupta, Ranjit Jhala

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Tags: Computer science, CUDA, nVidia, Programming Languages, Software Engineering

April 12, 2012 by hgpu

Full system simulation of many-core heterogeneous SoCs using GPU and QEMU semihosting

Shivani Raghav, Christian Pinto, Martino Ruggiero, Andrea Marongiu, David Atienza, Luca Benini

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Operating systems, Software Engineering, Tesla C2070

March 26, 2012 by hgpu

Synthesizing Software from a ForSyDe Model Targeting GPGPUs

Gabriel Hjort Blindell

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia Quadro FX 600, nVidia Quadro NVS 290, Software Engineering, Thesis

March 6, 2012 by hgpu

Reuse and Refactoring of GPU Kernels to Design Complex Applications

Santonu Sarkar, Sayantan Mitra, Ashok Srinivasan

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Tags: Computer science, CUDA, FFT, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Optimization, Software Engineering, Tesla S1050

February 24, 2012 by hgpu

Automatic SIMD Code Generation

Roland Leissa

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Tags: Algorithms, Code generation, Computer science, Optimization, Performance, Software Engineering, Thesis

January 4, 2012 by hgpu

Minimising Testing in Genetic Programming

W. B. Langdon

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, Software Engineering

December 15, 2011 by hgpu

GPU-Based Image Processing Use Cases: A High-Level Approach

Volkmar Wieser, Clemens Grelck, Holger Schoner, Peter Haslinger, Karoly Bosa, Bernhard Moser

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Tags: Benchmarking, CUDA, Image processing, nVidia, nVidia GeForce GT 425 M, Software Engineering, Virtualization

November 21, 2011 by hgpu

MELT-a Translated Domain Specific Language Embedded in the GCC Compiler

Basile Starynkevitch

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Tags: Compilers, Computer science, OpenCL, Optimization, Programming Languages, Software Engineering

November 7, 2011 by hgpu

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Muhammad Mustafa Rafique

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, Prefetch, Software Engineering, Tesla C2050, Thesis

October 28, 2011 by hgpu

Parallelization of Single Threaded Applications using OpenMP and CUDA/C

John Burns

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Tags: Computer science, CUDA, Databases, nVidia, OpenMP, Software Engineering

October 27, 2011 by hgpu

CUDA Application Design and Development

Rob Farber

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Tags: Book, Computer science, CUDA, nVidia, Review, Software Engineering

October 22, 2011 by hgpu

Numerical Accuracy Analysis Based on the Discrete Stochastic Arithmetic on Multiprocessor Platforms

Christian Motzing

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Tags: Computer science, CUDA, Molecular dynamics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Review, Software Engineering, Thesis

October 17, 2011 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

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high performance computing on graphics processing units: hgpu.org

Verifying GPU Kernels by Test Amplification

Full system simulation of many-core heterogeneous SoCs using GPU and QEMU semihosting

Synthesizing Software from a ForSyDe Model Targeting GPGPUs

Reuse and Refactoring of GPU Kernels to Design Complex Applications

Automatic SIMD Code Generation

Minimising Testing in Genetic Programming

GPU-Based Image Processing Use Cases: A High-Level Approach

MELT-a Translated Domain Specific Language Embedded in the GCC Compiler

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Parallelization of Single Threaded Applications using OpenMP and CUDA/C

CUDA Application Design and Development

Numerical Accuracy Analysis Based on the Discrete Stochastic Arithmetic on Multiprocessor Platforms

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CLUEstering: a high-performance density-based clustering library for scientific computing

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