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Comparison and Analysis of GPU Energy Efficiency For CUDA and OpenCL

Joe Jackson

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Tags: Computer science, CUDA, Energy-efficient computing, Matrix multiplication, nVidia, nVidia GeForce 9800 GT, OpenCL

July 8, 2013 by hgpu

Comparison of Rectangular Matrix Multiplication with and without Border Conditions

Petre Lameski, Igor Mishkovski, Sonja Filiposka, Dimitar Trajanov, Leonid Djinevski

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 680

July 7, 2013 by hgpu

GPU Matrix Multiplication

Junjie Li, Sanjay Ranka, Sartaj Sahni

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Tesla C1060

June 18, 2013 by hgpu

FastSpMM: An Efficient Library for Sparse Matrix Matrix Product on GPUs

Gloria Ortega, Francisco Vazquez, Inmaculada Garcia, Ester M. Garzon

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Source codes

Tags: Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 480, Package, Sparse matrix, Tesla C2050

June 12, 2013 by hgpu

Parallel Acceleration on Manycore Systems and Its Performance Analysis: OpenCL Case Study

Rafael Alejandro Vejarano, Phuong Thi Yen, Jeong-Gun Lee

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Tags: Computer science, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 460, OpenCL, Performance

June 4, 2013 by hgpu

Analyzing Locality of Memory References in GPU Architectures

Saurabh Gupta, Ping Xiang, Huiyang Zhou

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Tags: Computer science, GPGPU-sim, Matrix multiplication, nVidia, nVidia GeForce GTX 480

May 16, 2013 by hgpu

A portable and high-performance matrix operations library for CPUs, GPUs and beyond

Rahul Garg, Laurie Hendren

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 7970, Computer science, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Tesla C2050

May 11, 2013 by hgpu

GPU Sparse Matrix Multiplication with CUDA

Sean Rose

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tutorial

May 9, 2013 by hgpu

Improving Numerical Accuracy for Non-Negative Matrix Multiplication on GPUs using Recursive Algorithms

Matthew Badin, Paolo D'Alberto, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

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Tags: Algorithms, BLAS, Computer science, CUDA, Matrix multiplication, nVidia, Performance, Tesla C2070

April 30, 2013 by hgpu

Modeling and Optimization of Parallel Matrix-based Computations on GPU

Andrew White

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Optimization, Tesla S1070, Thesis

April 27, 2013 by hgpu

Co-processing SPMD Computation on GPUs and CPUs on Shared Memory System

Hui Li, Geoffrey Fox, Gregor Laszewski, Zhenhua Guo, Judy Qiu

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Tags: Clustering, CUDA, Heterogeneous systems, MapReduce, Matrix multiplication, nVidia

April 13, 2013 by hgpu

Optimizing Sparse Matrix-Matrix Multiplication for the GPU

Steven Dalton, Nathan Bell, Luke N. Olson

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Sorting, Sparse matrix, Tesla C2075

April 7, 2013 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Comparison and Analysis of GPU Energy Efficiency For CUDA and OpenCL

Comparison of Rectangular Matrix Multiplication with and without Border Conditions

GPU Matrix Multiplication

FastSpMM: An Efficient Library for Sparse Matrix Matrix Product on GPUs

Parallel Acceleration on Manycore Systems and Its Performance Analysis: OpenCL Case Study

Analyzing Locality of Memory References in GPU Architectures

A portable and high-performance matrix operations library for CPUs, GPUs and beyond

GPU Sparse Matrix Multiplication with CUDA

Improving Numerical Accuracy for Non-Negative Matrix Multiplication on GPUs using Recursive Algorithms

Modeling and Optimization of Parallel Matrix-based Computations on GPU

Co-processing SPMD Computation on GPUs and CPUs on Shared Memory System

Optimizing Sparse Matrix-Matrix Multiplication for the GPU

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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