high performance computing on graphics processing units: hgpu.org

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A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Hasmik Osipyan, Martin Krulis, Stephane Marchand-Maillet

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Tags: Algorithms, Computer science, CUDA, Machine learning, Multidimensional scaling, nVidia, nVidia GeForce GT 740 M, Pattern recognition

September 26, 2015 by hgpu

CFMDS: CUDA-based fast multidimensional scaling for genome-scale data

Sungin Park, Soo-Yong Shin, Kyu-Baek Hwang

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Tags: Bioinformatics, Biology, CUDA, Genetics, Multidimensional scaling, nVidia, Package

June 21, 2013 by hgpu

Visualization of large multidimensional data sets by using multi-core CPU, GPU and MPI cluster

Piotr Pawliczek, Witold Dzwinel, David A. Yuen

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Tags: Algorithms, Computer science, CUDA, Data mining, MPI, Multidimensional scaling, nVidia, nVidia GeForce 8500 GT, nVidia GeForce 8800 Ultra, nVidia GeForce 9500 GT, nVidia GeForce 9800 GT, nVidia GeForce GT 330 M, nVidia GeForce GTX 260, nVidia GeForce GTX 460, nVidia GeForce GTX 480, Tesla M2050, Visualization

October 6, 2012 by hgpu

Scattering Points in Parallel Coordinates

Xiaoru Yuan, Peihong Guo, He Xiao, Hong Zhou, Huamin Qu

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Tags: Computer science, CUDA, Multidimensional scaling, nVidia, Tesla C870, Visualization

November 28, 2010 by hgpu

Graphics Processing Units and High-Dimensional Optimization

Hua Zhou, Kenneth Lange, Marc A. Suchard

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Tags: Block relaxation, CUBLAS, CUDA, EM and MM algorithms, Mathematics, Multidimensional scaling, Nonnegative matrix factorization, nVidia, nVidia GeForce GTX 280, PET scanning, Statistics

October 30, 2010 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

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

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

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

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

CFMDS: CUDA-based fast multidimensional scaling for genome-scale data

Visualization of large multidimensional data sets by using multi-core CPU, GPU and MPI cluster

Scattering Points in Parallel Coordinates

Graphics Processing Units and High-Dimensional Optimization

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

nvsass-disassembler

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

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

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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