high performance computing on graphics processing units: hgpu.org

hgpu.org » Memory level parallelism

Scalable Kernel Fusion for Memory-Bound GPU Applications

Mohamed Wahib and Naoya Maruyama

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Tags: CUDA, Memory level parallelism, nVidia GeForce GTX 750 Ti, Tesla K20, Tesla K40

September 1, 2014 by wahibium

Resource-Aware Compiler Prefetching for Fine-Grained Many-Cores

George C. Caragea, Alexandros Tzannes, Fuat Keceli, Rajeev Barua, Uzi Vishkin

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Tags: Algorithms, ASIC, Benchmarking, Computer science, Memory level parallelism, nVidia, Package, Prefetch

December 29, 2011 by hgpu

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory level parallelism, nVidia, nVidia Quadro FX 5600, Warp level parallelism

December 15, 2011 by hgpu

Accelerating Parameter Sweep Applications Using CUDA

Masaya Motokubota, Fumihiko Ino, Kenichi Hagihara

Tags: Computer science, CUDA, Memory level parallelism, nVidia, Performance

June 14, 2011 by hgpu

An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Computer science, CUDA, Memory level parallelism, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTX, nVidia Quadro FX 5600, Warp level parallelism

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

Scalable Kernel Fusion for Memory-Bound GPU Applications

Resource-Aware Compiler Prefetching for Fine-Grained Many-Cores

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

Accelerating Parameter Sweep Applications Using CUDA

An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness

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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