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CLUEstering: a high-performance density-based clustering library for scientific computing

Simone Balducci

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Tags: Astrophysics, ATI, Clustering, CUDA, FPGA, HIP, Machine learning, nVidia, Package, performance portability, Physics, Python, Tesla T4, Thesis

December 1, 2024 by hgpu

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

Giulio Malenza, Valentina Cesare, Marco Edoardo Santimaria, Robert Birke, Alberto Vecchiato, Ugo Becciani, Marco Aldinucci

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Tags: AMD Radeon Instinct MI250X, Astrophysics, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, nVidia H100, nVidia V100, OpenMP, Package, Performance, performance portability, SYCL, Tesla T4

November 24, 2024 by hgpu

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

Lennart Steffen, Reinhard Hinkelmann

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, Intel, Intel Data Center GPU Max 1550, Linear Algebra, nVidia, nVidia A100, nVidia GeForce GTX Titan V, Package, performance portability

November 17, 2024 by hgpu

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Nathaniel Morgan, Caleb Yenusah, Adrian Diaz, Daniel Dunning,Jacob Moore,Erin Heilman, Calvin Roth, Evan Lieberman, Steven Walton, Sarah Brown, Daniel Holladay, Marko Knezevic, Gavin Whetstone, Zachary Baker, Robert Robey

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Tags: Computer science, CUDA, Fortran, HIP, nVidia, Package, performance portability, Pthreads

November 10, 2024 by hgpu

Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL

Manuel de Castro, Francisco J. andújar, Roberto R. Osorio, Rocío Carratalá-Sáez, Diego R. Llanos

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Tags: Computer science, FPGA, OpenCL, Optimization, performance portability, SYCL

September 22, 2024 by hgpu

Collection skeletons: declarative abstractions for data collections

Zhibo Li

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Tags: Computer science, Data Structures and Algorithms, OpenCL, performance portability, SYCL, Thesis

September 22, 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

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, CUDA, HIP, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia H100, oneAPI, Performance, performance portability, SYCL, Tesla A100, Tesla V100

August 14, 2024 by hgpu

Automatic Code Rewriting for Performance Portability

Alister Johnson

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Tags: Compilers, Computer science, HIP, OpenCL, OpenMP, performance portability, SYCL, Thesis

July 7, 2024 by hgpu

Experiences with implementing Kokkos’ SYCL backend

Daniel Arndt, Damien Lebrun-Grandie, Christian Trott

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Tags: Benchmarking, Computer science, HPC, Intel, Intel Data Center GPU Max 1550, Package, performance portability

May 5, 2024 by hgpu

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

John Tramm, Paul Romano, Patrick Shriwise, Amanda Lund, Johannes Doerfert, Patrick Steinbrecher, Andrew Siegel, Gavin Ridley

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, Intel, Intel Data Center GPU Max 1550, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, OpenMP, Package, performance portability

March 24, 2024 by hgpu

Retargeting and Respecializing GPU Workloads for Performance Portability

Ivan R. Ivanov, Oleksandr Zinenko, Jens Domke, Toshio Endo, William S. Moses

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Tags: AMD Radeon Instinct MI210, AMD Radeon RX 6800, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, nVidia RTX A4000, Package, performance portability

March 24, 2024 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

CLUEstering: a high-performance density-based clustering library for scientific computing

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL

Collection skeletons: declarative abstractions for data collections

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

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Automatic Code Rewriting for Performance Portability

Experiences with implementing Kokkos’ SYCL backend

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Retargeting and Respecializing GPU Workloads for Performance Portability

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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