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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

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

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

Addressing Challenges in Utilizing GPUs for Accelerating Privacy-Preserving Computation

Ardhi Wiratama Baskara Yudha

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, Security, Thesis

June 2, 2024 by hgpu

Evaluation of computational and energy performance in matrix multiplication algorithms on CPU and GPU using MKL, cuBLAS and SYCL

L.A. Torres, Carlos J. Barrios H, Yves Denneulin

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia A100, Package, Performance, SYCL

June 2, 2024 by hgpu

An implementation of tensor product patch smoothers on GPU

Cu Cui, Paul Grosse-Bley, Guido Kanschat, Robert Strzodka

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Tags: CUDA, FEM, Finite element method, Mathematics, Numerical Analysis, nVidia, nVidia A100

June 2, 2024 by hgpu

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

AFOCL

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

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high performance computing on graphics processing units: hgpu.org

A Survey of General-purpose Polyhedral Compilers

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

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

Addressing Challenges in Utilizing GPUs for Accelerating Privacy-Preserving Computation

Evaluation of computational and energy performance in matrix multiplication algorithms on CPU and GPU using MKL, cuBLAS and SYCL

An implementation of tensor product patch smoothers on GPU

Recent source codes

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

EnergyUCB-Bandit

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

miniLB: Lattice Botlzmann miniapp w/SYCL

AFOCL

2domination

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