high performance computing on graphics processing units: hgpu.org

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A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Lukas Einkemmer

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Tags: Computational Physics, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, Mixed precision, nVidia, OpenMP, Tesla K80

March 25, 2016 by hgpu

Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs

Wei Tan, Liangliang Cao, Liana Fong

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Factorization, nVidia, nVidia GeForce GTX Titan X, OpenMP, Tesla K80

March 15, 2016 by hgpu

Testing fine-grained parallelism for the ADMM on a factor-graph

Ning Hao, AmirReza Oghbaee, Mohammad Rostami, Nate Derbinsky, Jose Bento

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, Tesla K40

March 10, 2016 by hgpu

Alpaka – An Abstraction Library for Parallel Kernel Acceleration

Erik Zenker, Benjamin Worpitz, Rene Widera, Axel Huebl, Guido Juckeland, Andreas Knupfer, Wolfgang E. Nagel, Michael Bussmann

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Tags: Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, performance portability, Portability, Tesla K20, Tesla K80

March 1, 2016 by hgpu

Optimization of Molecular Dynamics Simulation Code and Applications to Biomolecular Systems

David M. Bowman

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Tags: Biochemistry, Biomolecules, Chemistry, CUDA, Molecular dynamics, MPI, nVidia, OpenCL, OpenMP, Thesis

March 1, 2016 by hgpu

Automatic and portable mapping of data parallel programs to OpenCL for GPU-based heterogeneous systems

Zheng Wang, Dominik Grewe, Michael F.P. O'Boyle

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, OpenMP, Performance

February 19, 2016 by hgpu

High performance high-order numerical methods: applications in ocean modeling

Rajesh Gandham

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Tags: ATI, ATI Radeon HD 7970, cfd, Computer science, CUDA, Fluid dynamics, Numerical simulation, nVidia, nVidia GeForce GTX Titan, OCCA, OpenCL, OpenMP, real time systems, Tesla C2050, Tesla K20, Tesla K40, Thesis

February 8, 2016 by hgpu

Optimization and Large Scale Computation of an Entropy-Based Moment Closure

C. Kristopher Garrett, Cory Hauck, Judith Hill

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Tags: Algorithms, CUDA, Heterogeneous systems, nVidia, OpenMP, Physics, Tesla K20

February 3, 2016 by hgpu

Extracting Flow Features Using Bag-of-Features and Supervised Learning Techniques

Yifei Li

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Tags: Algorithms, Clustering, Computer science, Computer vision, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, OpenMP, Package, Thesis, Visualization

February 2, 2016 by hgpu

High-Performance Tensor Contractions for GPUs

A. Abdelfattah, M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, Tz. Kolev, I. Masliah, S. Tomov

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Tags: Algorithms, Code generation, Computer science, CUDA, FEM, Finite element method, Linear Algebra, Matrix multiplication, nVidia, OpenMP, Tesla K40

January 29, 2016 by hgpu

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

Mohammed Abdelrahim

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Tags: Computer science, CUDA, Heterogeneous systems, LSTM, Machine learning, nVidia, nVidia GeForce GTX 770, OpenMP, Thesis

January 19, 2016 by hgpu

Real-Time Dedispersion for Fast Radio Transient Surveys, using Auto Tuning on Many-Core Accelerators

Alessio Sclocco, Joeri van Leeuwen, Henri E. Bal, Rob V. van Nieuwpoort

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Tags: Astrophysics, ATI, ATI Radeon HD 7970, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, nVidia, nVidia GeForce GTX 680, nVidia GeForce Titan, OpenCL, OpenMP, Package, Tesla K20

January 12, 2016 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs

Testing fine-grained parallelism for the ADMM on a factor-graph

Alpaka – An Abstraction Library for Parallel Kernel Acceleration

Optimization of Molecular Dynamics Simulation Code and Applications to Biomolecular Systems

Automatic and portable mapping of data parallel programs to OpenCL for GPU-based heterogeneous systems

High performance high-order numerical methods: applications in ocean modeling

Optimization and Large Scale Computation of an Entropy-Based Moment Closure

Extracting Flow Features Using Bag-of-Features and Supervised Learning Techniques

High-Performance Tensor Contractions for GPUs

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

Real-Time Dedispersion for Fast Radio Transient Surveys, using Auto Tuning on Many-Core Accelerators

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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