high performance computing on graphics processing units: hgpu.org

hgpu.org » Seismology

Assessing Accelerator-Based HPC Reverse Time Migration

Mauricio Araya-Polo, Javier Cabezas, Mauricio Hanzich, Miquel Pericas, Felix Rubio, Isaac Gelado, Muhammad Shafiq, Enric Morancho, Nacho Navarro, Eduard Ayguade, Jose M. Cela, Mateo Valero

Tags: Algorithms, Earth and Space Sciences, nVidia, Seismology

January 26, 2011 by hgpu

Accelerating 3D Fourier migration with graphics processing units

Jin H. Zhang, Shu Q. Wang, Zhen X. Yao

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Tags: CUDA, Earth and Space Sciences, FFT, Geoscience, nVidia, nVidia GeForce GTX 280, Seismology

January 19, 2011 by hgpu

Fluid-solid coupling on a cluster of GPU graphics cards for seismic wave propagation

Dimitri Komatitsch

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Tags: CUDA, Earth and Space Sciences, Finite element method, Geoscience, nVidia, Package, Seismic modeling, Seismology, Tesla S1070

January 16, 2011 by hgpu

Accelerating geoscience and engineering system simulations on graphics hardware

Stuart D. C. Walsh, Martin O. Saar, Peter Bailey, David J. Lilja

Tags: CUDA, Earth and Space Sciences, Geoscience, Lattice Boltzmann model, nVidia, Seismology

November 27, 2010 by hgpu

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

A Unified Intermediate Representation and Execution Architecture for Heterogeneous and Distributed Neural Simulation

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelLens: Deploying Triton Kernels to C++ Inference Engines

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

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