high performance computing on graphics processing units: hgpu.org

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Texture Cache Approximation on GPUs

Mark Sutherland, Joshua San Miguel, Natalie Enright Jerger

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Performance

July 3, 2015 by hgpu

Accelerating DNA Sequence Analysis using Intel Xeon Phi

Suejb Memeti, Sabri Pllana

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Tags: Bioinformatics, Computer science, Intel Xeon Phi, OpenMP, Performance

July 1, 2015 by hgpu

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Andre Viebke, Sabri Pllana

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Tags: CNN, Computer science, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Performance

July 1, 2015 by hgpu

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

Naveen Anand Subramaniam, Omkar Deshmukh, Vennila Megavannan, Dan Negrut

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 770, OpenCL, Performance, Sparse matrix, Tesla K20, Tesla K40

June 19, 2015 by hgpu

Visualization of OpenCL Application Execution on CPU-GPU Systems

Amir Kavyan Ziabari, Rafael Ubal, Dana Schaa, David Kaeli

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Tags: ARM, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Visualization

June 19, 2015 by hgpu

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

N. Sedaghati, A. Ashari, L. N. Pouchet, S. Parthasarathy, P. Sadayappan

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla K40

June 16, 2015 by hgpu

Performance of a code migration for the simulation of supersonic ejector flow to SMP, MIC and GPU using OpenMP, OpenMP+LEO, and OpenACC directives

C. Couder-Castaneda, H. Barrios-Pina, I. Gitler, M. Arroyo

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Tags: Computer science, Fortran, Intel Xeon Phi, nVidia, OpenACC, OpenMP, Performance, Tesla C2070

June 10, 2015 by hgpu

Meta-Programming and Auto-Tuning in the Search for High Performance GPU Code

Michael Vollmer, Bo Joel Svensson, Eric Holk, Ryan Newton

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Tags: Computer science, CUDA, nVidia, Performance, Search strategies, Tesla K40

June 7, 2015 by hgpu

Analysis of GPU Parallel Computing based on Matlab

Mingzhe Wang, Bo Wang, Qiu He, Xiuxiu Liu, Kunshuai Zhu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 540 M, Performance

May 28, 2015 by hgpu

A Performance and Scalability Analysis of the Tsunami Simulation EasyWave for Different Multi-Core Architectures and Programming Models

Steffen Christgau, Johannes Spazier, Bettina Schnor

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Tags: CUDA, Earth and Space Sciences, Geoscience, Intel Xeon Phi, MPI, nVidia, OpenMP, Package, Performance, Tesla K40

May 20, 2015 by hgpu

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

Gordon Inggs, David B. Thomas, Wayne Luk

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Tags: AMD FirePro W5000, ATI, Computational finance, Computer science, Finance, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia Grid K2, nVidia Quadro K4000, OpenCL, Option pricing, Performance

May 20, 2015 by hgpu

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Geoffrey Ndu, Javier Navaridas, Mikel Lujan

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Tags: Benchmarking, Computer science, FPGA, OpenCL, Package, Performance

May 19, 2015 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

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high performance computing on graphics processing units: hgpu.org

Texture Cache Approximation on GPUs

Accelerating DNA Sequence Analysis using Intel Xeon Phi

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

Visualization of OpenCL Application Execution on CPU-GPU Systems

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

Performance of a code migration for the simulation of supersonic ejector flow to SMP, MIC and GPU using OpenMP, OpenMP+LEO, and OpenACC directives

Meta-Programming and Auto-Tuning in the Search for High Performance GPU Code

Analysis of GPU Parallel Computing based on Matlab

A Performance and Scalability Analysis of the Tsunami Simulation EasyWave for Different Multi-Core Architectures and Programming Models

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

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