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Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core

Robert Jendersie, Christian Lessig, Thomas Richter

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Tags: Computer science, CUDA, Earth and Space Sciences, Finite element method, Numerical Analysis, nVidia, nVidia A100, nVidia GeForce RTX 3090, OpenMP, Package, PyTorch, SYCL

February 4, 2024 by hgpu

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

Andrea Montessori, Michele La Rocca, Giorgio Amati, Marco Lauricella, Adriano Tiribocchi, Sauro Succi

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Tags: cfd, CUDA, Fluid dynamics, HPC, Lattice Boltzmann model, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

February 4, 2024 by hgpu

Minuet: Accelerating 3D Sparse Convolutions on GPUs

Jiacheng Yang, Christina Giannoula, Jun Wu, Mostafa Elhoushi, James Gleeson, Gennady Pekhimenko

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Tags: Cloud, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3090, Package, Performance, PyTorch, Tesla A100

January 21, 2024 by hgpu

Efficiently Processing Large Relational Joins on GPUs

Bowen Wu, Dimitrios Koutsoukos, Gustavo Alonso

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Tags: Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

December 10, 2023 by hgpu

FIKIT: Priority-Based Real-time GPU Multi-tasking Scheduling with Kernel Identification

Wenqing Wu

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Tags: Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, nVidia GeForce RTX 4080 Ti, nVidia H100, Task scheduling

November 27, 2023 by hgpu

On the Three P’s of Parallel Programming for Heterogeneous Computing: Performance, Productivity, and Portability

Atharva Gondhalekar, Wu-chun Feng

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, nVidia, nVidia GeForce RTX 3090, oneAPI, OpenCL, Performance, performance portability, SYCL

November 12, 2023 by hgpu

Comparison of different n-body algorithms on various hardware platforms using SYCL

Tim Thüring

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Tags: AMD Radeon Pro VII, Astrophysics, ATI, Computer science, N-body simulation, nVidia, nVidia A100, nVidia GeForce RTX 3090, nVidia Quadro GP100, Package, Physics, SYCL, Thesis

October 15, 2023 by hgpu

Comparing Performance and Portability between CUDA and SYCL for Protein Database Search on NVIDIA, AMD, and Intel GPUs

Manuel Costanzo, Enzo Rucci, Carlos García Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, ATI, Bioinformatics, Biology, Computer science, CUDA, Intel, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3070, nVidia GeForce RTX 3090, oneAPI, Programming Languages, Smith-Waterman algorithm, SYCL, Tesla V100

September 24, 2023 by hgpu

A portable C++ library for memory and compute abstraction on multi-core CPUs and GPUs

Pietro Incardona, Aryaman Gupta, Serhii Yaskovets, Ivo F. Sbalzarini

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, OpenACC, OpenCL, OpenMP, Package, Performance, performance portability, SYCL

July 30, 2023 by hgpu

Towards a Benchmarking Suite for Kernel Tuners

Jacob O. Tørring, Ben van Werkhoven, Filip Petrovic, Floris-Jan Willemsen, Jirí Filipovic, Anne C. Elster

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Tags: Auto-Tuning, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3060, nVidia GeForce RTX 3090, nVidia Titan RTX, Package, performance portability

March 19, 2023 by hgpu

SaLoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs

Seongyeon Park, Hajin Kim, Tanveer Ahmad, Nauman Ahmed, Zaid Al-Ars, H. Peter Hofstee, Youngsok Kim, Jinho Lee

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Tags: Bioinformatics, Biology, CUDA, Databases, nVidia, nVidia GeForce GTX 1650, nVidia GeForce RTX 3090, Sequence alignment, Smith-Waterman algorithm, String matching

January 29, 2023 by hgpu

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks

Kun Wu, Mert Hidayetoğlu, Xiang Song, Sitao Huang, Da Zheng, Israt Nisa, Wen-mei Hwu

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce RTX 3090

January 22, 2023 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

Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

Efficiently Processing Large Relational Joins on GPUs

FIKIT: Priority-Based Real-time GPU Multi-tasking Scheduling with Kernel Identification

On the Three P’s of Parallel Programming for Heterogeneous Computing: Performance, Productivity, and Portability

Comparison of different n-body algorithms on various hardware platforms using SYCL

Comparing Performance and Portability between CUDA and SYCL for Protein Database Search on NVIDIA, AMD, and Intel GPUs

A portable C++ library for memory and compute abstraction on multi-core CPUs and GPUs

Towards a Benchmarking Suite for Kernel Tuners

SaLoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs

PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks

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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