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CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

Weifeng Liu, Brian Vinter

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Tags: Algorithms, AMD Radeon R9 290X, Benchmarking, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Performance, Sparse matrix

March 20, 2015 by hgpu

Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning

Ken Miura, Tatsuya Harada

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Tags: Algorithms, Computer science, Java, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, WebCL

March 20, 2015 by hgpu

Fast Sparse Matrix Multiplication on GPU

Lukas Polok, Viorela Ila, Pavel Smrz

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Sorting, Sparse matrix, Tesla K40

March 18, 2015 by hgpu

HELIOS-K: An Ultrafast, Open-source Opacity Calculator for Radiative Transfer

Simon L. Grimm, Kevin Heng

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Tags: Astrophysics, CUDA, Earth and Planetary Astrophysics, nVidia, Package, Tesla K20

March 14, 2015 by hgpu

Counting Triangles in Large Graphs on GPU

Adam Polak

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Tags: Clustering, Computer science, CUDA, Graph theory, MapReduce, nVidia, Package, Tesla C2050

March 3, 2015 by hgpu

MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Ken Miura, Tetsuaki Mano, Atsushi Kanehira, Yuichiro Tsuchiya, Tatsuya Harada

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Tags: Computer science, Java, Machine learning, Mathematical Software, OpenCL, Package, Python

March 2, 2015 by hgpu

Implementation of Smith-Waterman algorithm in OpenCL for GPUs

Dzmitry Razmyslovich, Guillermo Marcus, Markus Gipp, Marc Zapatka, Andreas Szillus

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Tags: Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sequence alignment, Smith-Waterman algorithm

February 27, 2015 by azhar ali

RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures

Sergey Voronin, Per-Gunnar Martinsson

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Tags: Algorithms, CUDA, CULA, Mathematical Software, Mathematics, Matrix decomposition, Numerical Analysis, nVidia, Package, Tesla M2070

February 22, 2015 by hgpu

Exploring Design Space of 3D NVM and eDRAM Caches Using DESTINY Tool (open-source code)

Sparsh Mittal, Matt Poremba, Jeffrey Vetter, Yuan Xie

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Tags: Architecture, area, cache, cpu, energy, GPGPU, latency modeling, Memory, Package

February 22, 2015 by sparsh0mittal

Reproducible Triangular Solvers for High-Performance Computing

Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat

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Tags: Algorithms, Computer science, Linear Algebra, nVidia, nVidia Quadro K5000, OpenCL, Package, Tesla K20

February 19, 2015 by hgpu

Memory-efficient Adaptive Subdivision for Software Rendering on the GPU

Thomas Weber

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Tags: ATI, ATI Radeon HD 7970, Computer science, OpenCL, Package, Rendering, Tessellation

February 19, 2015 by hgpu

NMF-mGPU: non-negative matrix factorization on multi-GPU systems

Edgardo Mejia-Roa, Daniel Tabas-Madrid, Javier Setoain, Carlos Garcia, Francisco Tirado, Alberto Pascual-Montano

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Factorization, GPU cluster, MPI, Nonnegative matrix factorization, nVidia, Package, Tesla C1060

February 19, 2015 by hgpu

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

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

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

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning

Fast Sparse Matrix Multiplication on GPU

HELIOS-K: An Ultrafast, Open-source Opacity Calculator for Radiative Transfer

Counting Triangles in Large Graphs on GPU

MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Implementation of Smith-Waterman algorithm in OpenCL for GPUs

RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures

Exploring Design Space of 3D NVM and eDRAM Caches Using DESTINY Tool (open-source code)

Reproducible Triangular Solvers for High-Performance Computing

Memory-efficient Adaptive Subdivision for Software Rendering on the GPU

NMF-mGPU: non-negative matrix factorization on multi-GPU systems

Recent source codes

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

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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