high performance computing on graphics processing units: hgpu.org

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Towards Chip-on-Chip Neuroscience: Fast Mining of Frequent Episodes Using Graphics Processors

Yong Cao, Debprakash Patnaik, Sean Ponce, Jeremy Archuleta, Patrick Butler, Wu-chun Feng, Naren Ramakrishnan

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Tags: Computer science, CUDA, Databases, Neuroscience, nVidia, nVidia GeForce GTX 280

December 27, 2010 by hgpu

Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets

Won-ki Jeong, Johanna Beyer, Student Member, Markus Hadwiger, Amelio Vazquez, Student Member, Hanspeter Pfister, Senior Member, Ross T. Whitaker

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Tags: Biology, Electron microscopy, Neuroscience, nVidia, nVidia Quadro FX 5800, Rendering, Tesla C1060

December 15, 2010 by hgpu

Automatic fitting of spiking neuron models to electrophysiological recordings

Cyrille Rossant, Dan F. Goodman, Jonathan Platkiewicz, Romain Brette

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Tags: Adaptive threshold, Biology, CUDA, Distributed computing, Neuroscience, nVidia, nVidia GeForce GTX 295, Optimization, Package

November 6, 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

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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

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

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

EinsummableV3 - graph-based computation with tensor operations support

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

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

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high performance computing on graphics processing units: hgpu.org

Towards Chip-on-Chip Neuroscience: Fast Mining of Frequent Episodes Using Graphics Processors

Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets

Automatic fitting of spiking neuron models to electrophysiological recordings

Recent source codes

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

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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

nvsass-disassembler

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

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

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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