high performance computing on graphics processing units: hgpu.org

Ilya Lashuk, Aparna Chandramowlishwaran, Harper Langston, Tuan-Anh nguyen, Rahul Sampath, Aashay Shringarpure, Richard Vuduc, Lexing Ying, Denis Zorin, George Biros

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Tags: Computer science, CUDA, Fast multipole method, Heterogeneous systems, MPI, nVidia, Programming techniques, Tesla M2070

July 5, 2012 by hgpu

Navigating An Evolutionary Fast Path to Exascale – Expanded Version

R.F. Barrett, S.D. Hammond, C.T. Vaughan, D.W. Doerfler, M.A. Heroux

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla M2090

July 5, 2012 by hgpu

Analyzing the CUDA Applications with its Latency and Bandwidth Tolerance

V.N. Pistulkar, C.A. Uttarwar

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Tags: Computer science, CUDA, GPU cluster, nVidia, PTX, Tesla C1060

July 5, 2012 by hgpu

Parallel Processing using FPGAs and GPUs

Abhijit Joshi

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, Tesla C2070, Thesis

July 3, 2012 by hgpu

Using OpenCL: Programming Massively Parallel Computers

Janusz Kowalik, Tadeusz Puzniakowski

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Tags: Book, Computer science, OpenCL, Tutorial

July 3, 2012 by hgpu

On the Use of GPUs in Realizing Cost-Effective Distributed RAID

Aleksandr Khasymski, M. Mustafa Rafique, Ali R. Butt, Sudharshan S. Vazhkudai, Dimitrios S. Nikolopoulos

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, Storage system, Tesla C2070

July 3, 2012 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

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

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

See all packages

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high performance computing on graphics processing units: hgpu.org

Fast algorithm of ray tracing based on KD-tree structure

Efficient Parallel RSA Decryption Algorithm for Many-core GPUs with CUDA

Parallel Particle Swarm Optimization on Graphical Processing Unit for Pose Estimation

Sparselet Models for Efficient Multiclass Object Detection

Parallel Memory Defragmentation on a GPU

High Performance System in GPU and CUDA Media Processing System

A Massively Parallel Adaptive Fast Multipole Method on Heterogeneous Architectures

Navigating An Evolutionary Fast Path to Exascale – Expanded Version

Analyzing the CUDA Applications with its Latency and Bandwidth Tolerance

Parallel Processing using FPGAs and GPUs

Using OpenCL: Programming Massively Parallel Computers

On the Use of GPUs in Realizing Cost-Effective Distributed RAID

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

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

PyOMP: OpenMP for Python in Numba

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