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Performance portability study of epistasis detection using SYCL on NVIDIA GPU

Zheming Jin, Jeffrey S. Vetter

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Tags: Computer science, CUDA, Genomics, nVidia, performance portability, SYCL, Tesla V100

October 9, 2022 by hgpu

Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Tsung-Wei Huang

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Tags: AMD Radeon RX 6900 XT, ATI, Computer science, Deep learning, nVidia, nVidia GeForce RTX 3090, OpenCL, performance portability, PyTorch, SYCL

September 11, 2022 by hgpu

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Jhe-Yu Liou, Muaaz Awan, Steven Hofmeyr, Stephanie Forrest, Carole-Jean Wu

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Tags: Bioinformatics, Biology, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti, Package, performance portability, Sequence alignment, Tesla P100, Tesla V100

September 4, 2022 by hgpu

Exploring Thread Coarsening on FPGA

Mostafa Eghbali Zarch, Reece Neff, Michela Becchi

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Tags: Compilers, Computer science, FPGA, OpenCL, Performance, performance portability

August 28, 2022 by hgpu

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs

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

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce RTX 2080 Ti, Package, performance portability, Programming Languages

July 10, 2022 by hgpu

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

John Keith Holmen

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX Titan X, performance portability, Task scheduling

June 5, 2022 by hgpu

Improving performance of SYCL applications on CPU architectures using LLVM-directed compilation flow

Pietro Ghiglio, Uwe Dolinsky, Mehdi Goli, Kumudha Narasimhan

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, performance portability, SYCL

May 1, 2022 by hgpu

Benchmarking a Proof-of-Concept Performance Portable SYCL-based Fast Fourier Transformation Library

Vincent R. Pascuzzi, Mehdi Goli

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, FFT, Heterogeneous systems, HIP, HPC, nVidia, nVidia A100, OpenCL, performance portability, SYCL

March 20, 2022 by hgpu

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Bo Qiao

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Tags: Code generation, Computer science, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce RTX 2080, OpenCL, Package, performance portability, Tesla K20, Thesis

January 2, 2022 by hgpu

Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability

Vincent R. Pascuzzi, Mehdi Goli

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Tags: AMD Radeon RX Vega 56, ATI, Computer science, Heterogeneous systems, nVidia, nVidia A100, performance portability, Pseudo-random number generators, SYCL

September 19, 2021 by hgpu

A Study of Mixed Precision Strategies for GMRES on GPUs

Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, performance portability, Tesla V100

September 19, 2021 by hgpu

Performance Portability and Evaluation of Heterogeneous Components of SeisSol Targeted to Upcoming Intel HPC GPUs

Ludwig Kratzl

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Intel, Intel UHD 630, MPI, nVidia, nVidia GeForce RTX 3090, OpenCL, Package, performance portability, SYCL, Thesis

August 29, 2021 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

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high performance computing on graphics processing units: hgpu.org

Performance portability study of epistasis detection using SYCL on NVIDIA GPU

Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Exploring Thread Coarsening on FPGA

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

Improving performance of SYCL applications on CPU architectures using LLVM-directed compilation flow

Benchmarking a Proof-of-Concept Performance Portable SYCL-based Fast Fourier Transformation Library

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability

A Study of Mixed Precision Strategies for GMRES on GPUs

Performance Portability and Evaluation of Heterogeneous Components of SeisSol Targeted to Upcoming Intel HPC GPUs

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

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