high performance computing on graphics processing units: hgpu.org

Ruibang Luo, Thomas Wong, Jianqiao Zhu, Chi-Man Liu, Edward Wu, Lap-Kei Lee, Haoxiang Lin, Wenjuan Zhu, David W. Cheung, Hing-Fung Ting, Siu-Ming Yiu, Chang Yu, Yingrui Li, Ruiqiang Li, Tak-Wah Lam

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, Package, Tesla C2070, Tesla M2050

February 25, 2013 by hgpu

Graphics Card as a Cheap Supercomputer

Jan Prikryl

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, Overview, Package

February 25, 2013 by hgpu

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

Kyungjoo Kim

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Tags: Computer science, CUDA, Factorization, FEM, Finite element method, Heterogeneous systems, nVidia, Package, Sparse direct solvers, Task scheduling, Tesla M2070

February 21, 2013 by hgpu

Chrono: a parallel multi-physics library for rigid-body, flexible-body, and fluid dynamics

H. Mazhar, T. Heyn, A. Pazouki, D. Melanz, A. Seidl, A. Bartholomew, A. Tasora, D. Negrut

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Tags: CUDA, Fluid dynamics, nVidia, Package, Physics, Visualization

February 21, 2013 by hgpu

ClusCo: clustering and comparison of protein models

Jamroz Michal, Kolinski Andrzej

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Tags: Biology, Biomolecules, Clustering, Computational Engineering, CUDA, Finance, nVidia, nVidia GeForce GTX 470, Package

February 20, 2013 by hgpu

Massively Parallel Computing in Economics

Eric M. Aldrich

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Tags: CUDA, Finance, nVidia, Package, Review, Stochastic simulation, Tesla C2075

February 15, 2013 by hgpu

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

S. J. Pennycook, S. A. Jarvis

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Tags: ATI, ATI FirePro V7800, ATI Radeon HD 6550, Benchmarking, Computer science, Molecular dynamics, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

February 14, 2013 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Packages

Symbolic Crosschecking of Data-Parallel Floating Point Code

clMAGMA: High Performance Dense Linear Algebra with OpenCL

High Performance GPU Accelerated Local Optimization in TSP

OpenOF: Framework for Sparse Non-linear Least Squares Optimization on a GPU

Acceleration of the MMFF94 routines within OpenBabel using Eigen and OpenCL

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

Graphics Card as a Cheap Supercomputer

Scheduling a Parallel Sparse Direct Solver to Multiple GPUs

Chrono: a parallel multi-physics library for rigid-body, flexible-body, and fluid dynamics

ClusCo: clustering and comparison of protein models

Massively Parallel Computing in Economics

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

Recent source codes

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

INT v.s. FP: A framework to compare low-bit integer and float-point formats

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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