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Adapting database components to heterogeneous environments

Dimitrios Koutsoukos

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia P100, Thesis

June 30, 2024 by hgpu

A Survey of General-purpose Polyhedral Compilers

Arun Thangamani, Vincent Loechner, Stéphane Genaud

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia A100, OpenCL, Package, survey

June 30, 2024 by hgpu

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Jacob O. Tørring, Carl Hvarfner, Luigi Nardi, Magnus Själander

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Tags: Benchmarking, Compilers, Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan V, nVidia Titan RTX, OpenCL, Package

June 30, 2024 by hgpu

Breaking the Memory Wall: A Study of I/O Patterns and GPU Memory Utilization for Hybrid CPU-GPU Offloaded Optimizers

Avinash Maurya, Jie Ye, M. Mustafa Rafique, Franck Cappello, Bogdan Nicolae

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Tags: Computer science, CUDA, LLM, Memory, nVidia, nVidia A100, nVidia H100, Performance

June 23, 2024 by hgpu

GPU Parallelization of Astronomical Image Subtraction

Gustav Arneving, Hugo Wilhelmsson

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Tags: Astrophysics, nVidia, nVidia GeForce GTX 1050, OpenCL, OpenMP, Physics, Thesis

June 23, 2024 by hgpu

Optimal Kernel Orchestration for Tensor Programs with Korch

Muyan Hu, Ashwin Venkatram, Shreyashri Biswas, Balamurugan Marimuthu, Bohan Hou, Gabriele Oliaro, Haojie Wang, Liyan Zheng, Xupeng Miao, Jidong Zhai

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Tags: Compilers, Computer science, CUDA, Neural networks, nVidia, nVidia A100, nVidia V100, Package, PyTorch

June 23, 2024 by hgpu

COOK Access Control on an embedded Volta GPU

Benjamin Lesage, Frédéric Boniol, Claire Pagetti

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia Jetson AGX Xavier

June 23, 2024 by hgpu

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

A methodology for comparing optimization algorithms for auto-tuning

Floris-Jan Willemsen, Richard Schoonhoven, Jiří Filipovič, Jacob O. Tørring, Rob van Nieuwpoort, Ben van Werkhoven

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Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3090, Package, Performance

June 16, 2024 by hgpu

How much can we gain from Tensor Kernel Fusion on GPUs?

Wei Sun, Ang Li, Sander Stuijk, Henk Corporaal

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Tags: Computer science, CUDA, Deep learning, Matrix multiplication, Neural networks, nVidia, nVidia A100, nVidia H100

June 16, 2024 by hgpu

Memory Interference and Performance Prediction in GPU-Accelerated Heterogeneous Systems

Alessio Masola

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 2080, nVidia Jetson AGX Xavier, Rendering, Thesis, Visualization

June 9, 2024 by hgpu

Gaining Cross-Platform Parallelism for HAL’s Molecular Dynamics Package using SYCL

Viktor Skoblin, Felix Höfling, Steffen Christgau

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Tags: AMD Radeon Instinct MI210, ATI, Computer science, CUDA, Molecular dynamics, nVidia, nVidia A100, nVidia A40, Package, Physics, SYCL

June 9, 2024 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

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

NVIDIA Nemotron Parse 1.1

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Adapting database components to heterogeneous environments

A Survey of General-purpose Polyhedral Compilers

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Breaking the Memory Wall: A Study of I/O Patterns and GPU Memory Utilization for Hybrid CPU-GPU Offloaded Optimizers

GPU Parallelization of Astronomical Image Subtraction

Optimal Kernel Orchestration for Tensor Programs with Korch

COOK Access Control on an embedded Volta GPU

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

A methodology for comparing optimization algorithms for auto-tuning

How much can we gain from Tensor Kernel Fusion on GPUs?

Memory Interference and Performance Prediction in GPU-Accelerated Heterogeneous Systems

Gaining Cross-Platform Parallelism for HAL’s Molecular Dynamics Package using SYCL

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

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

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