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Batched Linear Algebra Problems on GPU Accelerators

Tingxing Dong

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40, Thesis

January 4, 2016 by hgpu

CuMF: scale matrix factorization using just ONE machine with GPUs

Wei Tan, Liangliang Cao

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Tags: Computer science, CUDA, Data parallelism, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX Titan X

December 6, 2015 by hgpu

Design, Implementation and Performance Evaluation of a Stochastic Gradient Descent Algorithm on CUDA

Emanuele De Falco

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GT 540 M

November 29, 2015 by hgpu

A general tridiagonal solver for coprocessors: Adapting g-Spike for the Intel Xeon Phi

Ioannis E. Venetis, Alexandros Sobczyk, Alexandros Kouris, Alexandros Nakos, Nikolaos Nikoloutsakos, Efstratios Gallopoulos

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Tags: Computer science, Factorization, Intel Xeon Phi, Linear Algebra, nVidia

October 31, 2015 by hgpu

MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing

Azzam Haidar, Stanimire Tomov, Piotr Luszczek, Jack Dongarra

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia Jetson TK1, Package

October 6, 2015 by hgpu

Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines

Terry Cojean, Abdou Guermouche, Andra Hugo, Raymond Namyst, Pierre-Andre Wacrenier

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, OpenMP, Task scheduling, Tesla K40

August 5, 2015 by hgpu

Flexible Linear Algebra Development and Scheduling with Cholesky Factorization

Azzam Haidar, Chongxiao Cao, Stanimire Tomov, Asim YarKhan, Piotr Luszczek, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, nVidia, Tesla M2090

August 5, 2015 by hgpu

Dense Symmetric Indefinite Factorization on GPU Accelerated Architectures

Marc Baboulin, Jack Dongarra, Adrien Remy, Stanimire Tomov, Ichitaro Yamazaki

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40

August 5, 2015 by hgpu

Bulk GCD Computation Using a GPU to Break Weak RSA Keys

Toru Fujita, Koji Nakano, Yasuaki Ito

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 780 Ti, Security

June 19, 2015 by hgpu

Algorithm 9xx: Sparse QR Factorization on the GPU

Sencer Nuri Yeralan, Timothy A. Davis, Sanjay Ranka

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Package, Sparse matrix, Tesla C2070

April 25, 2015 by hgpu

Framework for Batched and GPU-resident Factorization Algorithms Applied to Block Householder Transformations

Azzam Haidar, Tingxing "Tim" Dong, Stanimire Tomov, Piotr Luszczek, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

April 12, 2015 by hgpu

Batched Matrix Computations on Hardware Accelerators

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40

April 12, 2015 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Batched Linear Algebra Problems on GPU Accelerators

CuMF: scale matrix factorization using just ONE machine with GPUs

Design, Implementation and Performance Evaluation of a Stochastic Gradient Descent Algorithm on CUDA

A general tridiagonal solver for coprocessors: Adapting g-Spike for the Intel Xeon Phi

MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing

Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines

Flexible Linear Algebra Development and Scheduling with Cholesky Factorization

Dense Symmetric Indefinite Factorization on GPU Accelerated Architectures

Bulk GCD Computation Using a GPU to Break Weak RSA Keys

Algorithm 9xx: Sparse QR Factorization on the GPU

Framework for Batched and GPU-resident Factorization Algorithms Applied to Block Householder Transformations

Batched Matrix Computations on Hardware Accelerators

Recent source codes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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