high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

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

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

Parallel Gaussian process with kernel approximation in CUDA

Davide Carminati

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Tags: Benchmarking, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1050, nVidia GeForce RTX 2080, Package

March 24, 2024 by hgpu

Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors

Andres E. Tomas, Enrique S. Quintana-Orti, Hartwig Anzt

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia A100

March 18, 2024 by hgpu

Cost-Effective Methodology for Complex Tuning Searches in HPC: Navigating Interdependencies and Dimensionality

Adrian Perez Dieguez, Min Choi, Mahmut Okyay, Mauro Del Ben, Bryan M. Wong, Khaled Z. Ibrahim

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Tags: Computer science, CUDA, HPC, MPI, nVidia, nVidia A100, OpenMP, Performance

March 18, 2024 by hgpu

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

Youssef Faqir-Rhazoui, Carlos García

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Tags: Computer science, CUDA, nVidia, nVidia Jetson Orin Nano, Optical flow, Package, Performance, SYCL

March 18, 2024 by hgpu

Parallel Implementation of Lightweight Secure Hash Algorithm on CPU and GPU Environments

Hojin Choi, SeongJun Choi, SeogChung Seo

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3090, Package, PTX, Security

March 10, 2024 by hgpu

Using AI libraries for Incompressible Computational Fluid Dynamics

Boyang Chen, Claire E. Heaney, Christopher C. Pain

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Tags: AI, Artificial intelligence, cfd, CUDA, Fluid dynamics, Neural networks, nVidia, Partial differential equations, PDEs, Tesla T4

March 3, 2024 by hgpu

Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks

Kade M. Heckel, Thomas Nowotny

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia RTX A6000, Package, Python

March 3, 2024 by hgpu

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

Sébastien Darche, Michel R. Dagenais

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, CUDA, HIP, nVidia, Package, Performance, Profiling

March 3, 2024 by hgpu

Parallel programming in mobile devices with FancyJCL

Sergio Afonso, Óscar Gómez-Cárdenes, Paula Expósito, Vicente Blanco, Francisco Almeida

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Tags: Computer science, DSP, Heterogeneous systems, Image processing, Java, OpenCL, Package

March 3, 2024 by hgpu

APPy: Annotated Parallelism for Python on GPUs

Tong Zhou, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce RTX 3090, Python

February 25, 2024 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

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

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Programming

Retargeting and Respecializing GPU Workloads for Performance Portability

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

Parallel Gaussian process with kernel approximation in CUDA

Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors

Cost-Effective Methodology for Complex Tuning Searches in HPC: Navigating Interdependencies and Dimensionality

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

Parallel Implementation of Lightweight Secure Hash Algorithm on CPU and GPU Environments

Using AI libraries for Incompressible Computational Fluid Dynamics

Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

Parallel programming in mobile devices with FancyJCL

APPy: Annotated Parallelism for Python on GPUs

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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