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A Hybrid Framework for Fast and Accurate GPU Performance Estimation through Source-Level Analysis and Trace-Based Simulation

Xiebing Wang, Kai Huang, Alois Knoll, Xuehai Qian

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Tags: Computer science, nVidia, nVidia GeForce GTX 645, nVidia GeForce GTX 940 M, nVidia Quadro K600, nVidia Quadro K620, OpenCL, Performance

May 26, 2019 by hgpu

Data Layout Oriented Compilation Techniques in Vectorization for Multi-/Many-cores

Shixiong Xu

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 645, nVidia Jetson TK1

September 9, 2017 by hgpu

Exploiting Hyper-Loop Parallelism in Vectorization to Improve Memory Performance on CUDA GPGPU

Shixiong Xu, David Gregg

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Tags: ARM, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 645, nVidia Jetson TK1

September 3, 2015 by hgpu

Optimizing Urban Environmental Simulations using Boinc

Aditya Vegesna

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Tags: Computer science, CUDA, Earth and Space Sciences, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 645, Thesis

September 29, 2013 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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high performance computing on graphics processing units: hgpu.org

A Hybrid Framework for Fast and Accurate GPU Performance Estimation through Source-Level Analysis and Trace-Based Simulation

Data Layout Oriented Compilation Techniques in Vectorization for Multi-/Many-cores

Exploiting Hyper-Loop Parallelism in Vectorization to Improve Memory Performance on CUDA GPGPU

Optimizing Urban Environmental Simulations using Boinc

Recent source codes

ATTUNE: Agentic Throughput Tuning for LLM Training

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

Brian2 Atlas

AgentGarten: Code Worlds for Evolving Agents

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

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

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