Matrix multiplication | Page 14

hgpu.org » Matrix multiplication

Energy Efficiency Studies of Mont Blanc Applications

Mads Holden

View

Download (PDF)

Source codes

Tags: ARM, Computer science, Energy-efficient computing, Matrix multiplication, OpenCL, Package, Thesis

October 21, 2013 by hgpu

Optimal Configuration of GPU Cache Memory to Maximize the Performance

Leonid Djinevski, Sime Arsenovski, Sasko Ristov, Marjan Gusev

View

Download (PDF)

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

September 16, 2013 by hgpu

Analysis-Driven Design of Parallel Floating-Point Matrix Multiplication for Implementation in Reconfigurable Logic

Ahmad Khayyat

View

Download (PDF)

Tags: Computer science, FPGA, Matrix multiplication, Thesis

August 24, 2013 by hgpu

Performance Drawbacks for Matrix Multiplication using Set Associative Cache in GPU devices

Leonid Djinevski, Sime Arsenovski, Sasko Ristov, Marjan Gusev

View

Download (PDF)

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

August 19, 2013 by hgpu

GPU Programming in Functional Languages: A Comparison of Haskell GPU Embedded Domain Specific Languages

C. Ouwehand, P. Hijma, W.J. Fokkink

View

Download (PDF)

Tags: Computer science, CUDA, Haskell, Matrix multiplication, nVidia, nVidia GeForce GTX 480

August 6, 2013 by hgpu

OpenCL API Extensions to achieve Multi-level Parallelism for Efficient Implementation of Strassen’s Matrix Multiplication on GPUs

Sivaramakrishnan Kasiviswanathan

View

Download (PDF)

Tags: Algorithms, Computer science, Data parallelism, Matrix multiplication, nVidia, OpenCL, Tesla K20

July 19, 2013 by hgpu

On Benchmarking the Matrix Multiplication Algorithm using OpenMP, MPI and CUDA Programming Languages

Muhammed Al-Mulhem, Abdulah AlDhamin, Raed Al-Shaikh

View

Download (PDF)

Tags: Algorithms, Benchmarking, Bioinformatics, Computer science, CUDA, Linear Algebra, Matrix multiplication, MPI, nVidia, nVidia GeForce GTX 460

July 19, 2013 by hgpu

CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs

C. E. Castro, J. Behrens, C. Pelties

View

Download (PDF)

Tags: CUDA, Differential equations, Earth and Space Sciences, Geoscience, Hyperbolic PDEs, Matrix multiplication, nVidia, Partial differential equations, PDEs, Tesla C2070

July 15, 2013 by hgpu

Comparison and Analysis of GPU Energy Efficiency For CUDA and OpenCL

Joe Jackson

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

Source codes

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

June 12, 2013 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Energy Efficiency Studies of Mont Blanc Applications

Optimal Configuration of GPU Cache Memory to Maximize the Performance

Analysis-Driven Design of Parallel Floating-Point Matrix Multiplication for Implementation in Reconfigurable Logic

Performance Drawbacks for Matrix Multiplication using Set Associative Cache in GPU devices

GPU Programming in Functional Languages: A Comparison of Haskell GPU Embedded Domain Specific Languages

OpenCL API Extensions to achieve Multi-level Parallelism for Efficient Implementation of Strassen’s Matrix Multiplication on GPUs

On Benchmarking the Matrix Multiplication Algorithm using OpenMP, MPI and CUDA Programming Languages

CUDA-C implementation of the ADER-DG method for linear hyperbolic PDEs

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

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Most viewed papers (last 30 days)