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An abstract object oriented runtime system for heterogeneous parallel architecture

Jean-Marc Gratien

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2070, Tesla T10

February 20, 2013 by hgpu

Accelerating encryption using commodity hardware

Grigore Lupescu

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Tags: Computer science, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 580, OpenCL, Security

February 18, 2013 by hgpu

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Shuaiwen Song, Chunyi Su, Barry Rountree, Kirk W. Cameron

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Tags: Biomolecules, Computer science, CUDA, Electrostatics, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, Tesla C2075, Tesla M2090

February 18, 2013 by hgpu

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Chris J. Newburn, Rajiv Deodhar, Serguei Dmitriev, Ravi Murty, Ravi Narayanaswamy, John Wiegert, Francisco Chinchilla, Russell McGuire

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Tags: Compilers, Computer science, Heterogeneous systems, Intel, Intel Phi, Programming techniques

February 18, 2013 by hgpu

Formalizing Address Spaces with application to Cuda, OpenCL, and beyond

Benedict R. Gaster

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Tags: Computer science, OpenCL

February 18, 2013 by hgpu

Hybrid parallel programming – evaluation of OpenACC

Leonardo Piletti Chatain

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Tags: Benchmarking, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 480, OpenACC, Thesis

February 15, 2013 by hgpu

pROST : A Smoothed Lp-norm Robust Online Subspace Tracking Method for Realtime Background Subtraction in Video

Florian Seidel, Clemens Hage, Martin Kleinsteuber

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 660 Ti

February 15, 2013 by hgpu

MATLAB and Python for GPU Computing

Jose Unpingco, Juan Carlos Chaves

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 9800 GTS, nVidia GeForce 9800 GX2, Python, Signal processing, Tesla C1060, Tesla C2050

February 15, 2013 by hgpu

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

S. J. Pennycook, S. A. Jarvis

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Source codes

Tags: ATI, ATI FirePro V7800, ATI Radeon HD 6550, Benchmarking, Computer science, Molecular dynamics, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

February 14, 2013 by hgpu

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

S. J. Pennycook, C. J. Hughes, M. Smelyanskiy, S. A. Jarvis

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Tags: Algorithms, Benchmarking, Computer science, Intel, Intel Phi, Molecular dynamics

February 14, 2013 by hgpu

Enhancing Performance of Meshfree Methods by Hybrid Computing

Yo-Ming Hsieh, Mao-Sen Pan

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Tags: Computer science, CUDA, FEM, Finite element method, Hybrid computing, nVidia, Tesla C2050

February 14, 2013 by hgpu

The Dual-Path Execution Model for Efficient GPU Control Flow

Minsoo Rhu, Mattan Erez

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Performance

February 14, 2013 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Applications

An abstract object oriented runtime system for heterogeneous parallel architecture

Accelerating encryption using commodity hardware

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Offload Compiler Runtime for the Intel Xeon Phi Coprocessor

Formalizing Address Spaces with application to Cuda, OpenCL, and beyond

Hybrid parallel programming – evaluation of OpenACC

pROST : A Smoothed Lp-norm Robust Online Subspace Tracking Method for Realtime Background Subtraction in Video

MATLAB and Python for GPU Computing

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

Enhancing Performance of Meshfree Methods by Hybrid Computing

The Dual-Path Execution Model for Efficient GPU Control Flow

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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