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

November 5, 2010 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

Hardware-Aware FP4 FlashAttention-4

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

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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

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

EinsummableV3 - graph-based computation with tensor operations support

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