high performance computing on graphics processing units: hgpu.org

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Using modern C++ to improve CUDA programs

Mythreya Kuricheti

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Tags: Computer science, CUDA, nVidia, nVidia Quadro RTX 5000, Performance, PTX, Thesis

October 27, 2024 by hgpu

Enhancing Code Portability, Problem Scale, and Storage Efficiency in Exascale Applicationsin Exascale Applications

Nigel Tan

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Tags: AMD Radeon Vega VII, ATI, Computer science, CUDA, Heterogeneous systems, HPC, nVidia, nVidia A100, nVidia DGX-A100, nVidia Quadro RTX 5000, OpenMP, OpenMPI, Particle-in-cell methods, performance portability, Tesla V100, Thesis

September 15, 2024 by hgpu

Automating Heterogeneous Parallelism in Numerical Differential Equations

Utkarsh

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, Differential equations, Factorization, Heterogeneous systems, Intel, Intel Arc A770, Julia, Numerical Analysis, nVidia, nVidia Quadro RTX 5000, Package, Tesla V100, Thesis

July 14, 2024 by hgpu

Comparing SYCL data transfer strategies for tracking use cases

S.Joube, H. Grasland, D. Chamont, E.Brunet

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Tags: Benchmarking, Computer science, Memory model, nVidia, nVidia Quadro RTX 5000, SYCL

March 26, 2023 by hgpu

A Variant of Concurrent Constraint Programming on GPU

Pierre Talbot, Frederic Pinel, Pascal Bouvry

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Tags: Computer science, CUDA, nVidia, nVidia Quadro RTX 5000, Package, Performance

January 2, 2022 by hgpu

Predictive Data Race Detection for GPUs

Sagnik Dey, Mayant Mukul, Parth Sharma, Swarnendu Biswas

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro RTX 5000, Performance

November 28, 2021 by hgpu

AsymML: An Asymmetric Decomposition Framework for Privacy-Preserving DNN Training and Inference

Yue Niu, Ramy E. Ali, Salman Avestimehr

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Tags: Computer science, Neural networks, nVidia, nVidia Quadro RTX 5000, Security

October 10, 2021 by hgpu

Literature Review and Implementation Overview: High Performance Computing with Graphics Processing Units for Classroom and Research Use

Nathan George

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Tags: Computer science, CUDA, Deep learning, Education, GPU cluster, HPC, nVidia, nVidia GeForce GTX 1080 Ti, nVidia Quadro RTX 5000, Overview

May 24, 2020 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

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

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

See all packages

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high performance computing on graphics processing units: hgpu.org

Using modern C++ to improve CUDA programs

Enhancing Code Portability, Problem Scale, and Storage Efficiency in Exascale Applicationsin Exascale Applications

Automating Heterogeneous Parallelism in Numerical Differential Equations

Comparing SYCL data transfer strategies for tracking use cases

A Variant of Concurrent Constraint Programming on GPU

Predictive Data Race Detection for GPUs

AsymML: An Asymmetric Decomposition Framework for Privacy-Preserving DNN Training and Inference

Literature Review and Implementation Overview: High Performance Computing with Graphics Processing Units for Classroom and Research Use

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

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

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