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Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies

Johannes Pekkilä, Oskar Lappi, Fredrik Robertsén, Maarit J. Korpi-Lagg

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, Energy-efficient computing, HIP, nVidia, nVidia A100, nVidia V100, Package, Performance, PyTorch, Stencil computation

June 16, 2024 by hgpu

Helix: Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs

Yixuan Mei, Yonghao Zhuang, Xupeng Miao, Juncheng Yang, Zhihao Jia, Rashmi Vinayak

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Tags: Computer science, GPU cluster, Heterogeneous systems, nVidia, nVidia A100, nVidia V100, Tesla T4

June 9, 2024 by hgpu

Kernel-Centric Optimizations for Deep Neural Networks on GPGPU

Zhaodong Chen

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Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia A100, nVidia V100, Thesis

May 26, 2024 by hgpu

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

Martin Karp

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, Fluid dynamics, FPGA, Heterogeneous systems, Numerical simulation, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, Spectral elements, Thesis

May 12, 2024 by hgpu

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

Peter Thoman, Philip Salzmann

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Tags: Benchmarking, Computer science, GPU cluster, HPC, nVidia, nVidia V100, Package, SYCL

April 14, 2024 by hgpu

Speed, power and cost implications for GPU acceleration of Computational Fluid Dynamics on HPC systems

Zachary Cooper-Baldock, Brenda Vara Almirall, Kiao Inthavong

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Tags: cfd, Fluid dynamics, HPC, MPI, nVidia, nVidia A100, nVidia V100, Performance

April 7, 2024 by hgpu

FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators

Xinyi Li, Ang Li, Bo Fang, Katarzyna Swirydowicz, Ignacio Laguna, Ganesh Gopalakrishnan

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, ATI, Computer science, Hardware Architecture, HPC, Matrix multiplication, nVidia, nVidia A100, nVidia H100, nVidia V100, PTX

March 10, 2024 by hgpu

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

Manuel Costanzo, Enzo Rucci, Carlos García-Sanchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, AMD Radeon RX Vega 6, ATI, Bioinformatics, Biology, Computational biology, CUDA, Heterogeneous systems, Intel Arc A770, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, nVidia V100, oneAPI, Package, Sequence alignment, SYCL

February 25, 2024 by hgpu

TransAxx: Efficient Transformers with Approximate Computing

Dimitrios Danopoulos, Georgios Zervakis, Dimitrios Soudris, Jörg Henkel

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia V100, Package, PyTorch

February 18, 2024 by hgpu

An Evaluative Comparison of Performance Portability across GPU Programming Models

Joshua H. Davis, Pranav Sivaraman, Isaac Minn, Konstantinos Parasyris, Harshitha Menon, Giorgis Georgakoudis, Abhinav Bhatele

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct Mi50, ATI, Computer science, CUDA, Heterogeneous systems, HIP, MPI, nVidia, nVidia V100, OpenACC, OpenMP, Performance, performance portability, SYCL

February 18, 2024 by hgpu

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

Ka Hei Martin Kwok, Matti Kortelainen, Giuseppe Cerati, Alexei Strelchenko, Oliver Gutsche, Allison Reinsvold Hall, Steve Lantz, Michael Reid, Daniel Riley, Sophie Berkman, Seyong Lee, Hammad Ather, Boyana Norris, Cong Wang

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Tags: AMD Radeon Instinct MI100, ATI, HEP, Intel, Intel Arc A770, nVidia, nVidia A100, nVidia V100, OpenMP, performance portability, Physics, SYCL

January 28, 2024 by hgpu

MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky

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Tags: Compression, Computer science, CUDA, HIP, HPC, Numerical Analysis, nVidia, nVidia V100, OpenMP, Package, SYCL

January 21, 2024 by hgpu

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

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

Concurrent Scheduling of High-Level Parallel Programs on Multi-GPU Systems

wgpy: WebGL accelerated numpy-compatible array library for web browser

WgPy: GPU-accelerated NumPy-like array library for web browsers

Microbenchmarking OpenMP target offload with Catch2

A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading

SUperman: Highly Efficient Permanent Computation Library

SUperman: Efficient Permanent Computation on GPUs

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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