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hgpu.org » Particle physics and field theory

GPGPU opportunities for the LHCb trigger

Alexey Badalov, Daniel Campora, Gianmaria Collazuol, Marco Corvo, Stefano Gallorini, Alessio Gianelle, Elisabet Golobardes, Donatella Lucchesi, Anna Lupato, Niko Neufeld, Lorenzo Sestini, Rainer Schwemmer, Xavier Vilasis-Cardona

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Tags: CUDA, High Energy Physics - Experiment, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, Particle physics and field theory, Physics

June 6, 2014 by hgpu

GPU-Based Tracking Algorithms for the ATLAS High-Level Trigger

D. Emeliyanov, J. Howard

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Tags: CUDA, Data acquisition, Instrumentation and measurement, Nuclear physics, nVidia, Particle physics and field theory, Physics, Tesla C2050

December 29, 2012 by hgpu

Track finding in ATLAS using GPUs

J. Mattmann and C. Schmitt

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Tags: Algorithms, CUDA, Instrumentation and measurement, Nuclear physics, nVidia, Particle physics and field theory, Physics

December 20, 2012 by hgpu

IceCubes GPGPU’s cluster for extensive MC production

Martin Merck, Dmitry Chirkin, Juan Carlos Diaz Velez, Heath Skarlupka

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Tags: Computational Physics, CUDA, GPU cluster, Monte Carlo simulation, Nuclear physics, nVidia, Particle physics and field theory, Physics, Raytracing, Tesla M2070

December 20, 2012 by hgpu

GPU’s for event reconstruction in the FairRoot framework

M. {Al-Turany}, F. {Uhlig}, R. {Karabowicz}

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Source codes

Tags: CUDA, Instrumentation and measurement, Nuclear physics, nVidia, Package, Particle physics and field theory, Physics, Tesla C1060

November 5, 2010 by hgpu

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

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high performance computing on graphics processing units: hgpu.org

GPGPU opportunities for the LHCb trigger

GPU-Based Tracking Algorithms for the ATLAS High-Level Trigger

Track finding in ATLAS using GPUs

IceCubes GPGPU’s cluster for extensive MC production

GPU’s for event reconstruction in the FairRoot framework

Recent source codes

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

exa-AMD: Exascale Accelerated Materials Discovery

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