high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Solving very large instances of the scheduling of independent tasks problem on the GPU

Frederic Pinel, Bernabe Dorronsoro, Pascal Bouvry

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Tags: Computer science, CUDA, nVidia, Task scheduling, Tesla C2050

August 3, 2012 by hgpu

Power Management for GPU-CPU Heterogeneous Systems

Xue Li

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, Thesis

August 3, 2012 by hgpu

GPU-to-GPU and Host-to-Host multipattern string matching on a GPU

Xinyan Zha, Sartaj Sahni

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Tags: Algorithms, Computer science, CUDA, nVidia, String matching, Tesla

August 3, 2012 by hgpu

Parallel Statistical Analysis of Analog Circuits by GPU-accelerated Graph-based Approach

Xue-Xin Liu, Sheldon X.-D. Tan, Hai Wang

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Tags: Computer science, CUDA, Data parallelism, Electronic design automation, nVidia, Tesla C2070

August 3, 2012 by hgpu

Performance Analysis of GPU Accelerators with Realizable Utilization of Computational Density

Justin Richardson, Alan D. George, Herman Lam

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Tags: Computer science, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GT 240, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance, Tesla C1060, Tesla C870

August 3, 2012 by hgpu

Automated Tool to Generate Parallel CUDA code from a Serial C Code

Akhil Jindal, Nikhil Jindal, Divyashikha Sethia

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce 8400 GS

August 2, 2012 by hgpu

C to Cellular Automata and Execution on CPU, GPU and FPGA

Jens Drieseberg, Christian Siemers

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Tags: Cellular automata, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 580, OpenMP

August 2, 2012 by hgpu

Interference-driven resource management for GPU-based heterogeneous clusters

Rajat Phull, Cheng-Hong Li, Kunal Rao, Srihari Cadambi, Srimat Chakradhar

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, PC cluster, Performance, Tesla C2050

August 1, 2012 by hgpu

GPU merge path: a GPU merging algorithm

Oded Green, Robert McColl, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Tesla C1060, Tesla C2070

August 1, 2012 by hgpu

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

Neelima Reddy, Raghavendra Prakash, Ram Mohana Reddy

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 470, Sparse matrix

August 1, 2012 by hgpu

High-Level Manipulation of OpenCL-Based Subvectors and Submatrices

Karl Rupp

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Tags: Computer science, Factorization, nVidia, nVidia GeForce GTX 470, OpenCL

August 1, 2012 by hgpu

GPU-Accelerated Non-negative Matrix Factorization for Text Mining

Volodymyr Kysenko, Karl Rupp, Oleksandr Marchenko, Siegfried Selberherr, Anatoly Anisimov

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Computer science, Factorization, Nonnegative matrix factorization, nVidia, nVidia GeForce GTX 470, OpenCL, Text mining

August 1, 2012 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

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

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Solving very large instances of the scheduling of independent tasks problem on the GPU

Power Management for GPU-CPU Heterogeneous Systems

GPU-to-GPU and Host-to-Host multipattern string matching on a GPU

Parallel Statistical Analysis of Analog Circuits by GPU-accelerated Graph-based Approach

Performance Analysis of GPU Accelerators with Realizable Utilization of Computational Density

Automated Tool to Generate Parallel CUDA code from a Serial C Code

C to Cellular Automata and Execution on CPU, GPU and FPGA

Interference-driven resource management for GPU-based heterogeneous clusters

GPU merge path: a GPU merging algorithm

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

High-Level Manipulation of OpenCL-Based Subvectors and Submatrices

GPU-Accelerated Non-negative Matrix Factorization for Text Mining

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

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

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