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Building-Blocks for Performance Oriented DSLs

Tiark Rompf, Arvind K. Sujeeth, HyoukJoong Lee, Kevin J. Brown, Hassan Chafi, Martin Odersky, Kunle Olukotun

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Programming Languages, Tesla C2050

November 23, 2011 by hgpu

TEG: GPU Performance Estimation Using a Timing Model

Junjie Lai, Andre Seznec

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance

November 23, 2011 by hgpu

Dynamic adaptation and distribution of binaries to heterogeneous architectures

Espen Angell Kristiansen

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GT 220, nVidia GeForce GTX 280, OpenCL, Package, Playstation, Thesis

November 22, 2011 by hgpu

Dynamic Heterogeneous Scheduling Decisions Using Historical Runtime Data

Chris Gregg, Michael Boyer, Kim Hazelwood, Kevin Skadron

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Tags: ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, OpenCL, Performance, Task scheduling

November 22, 2011 by hgpu

Parallelizing Multicore Cache Simulations using Heterogeneous Computing on General Purpose and Graphics Processors

Nikolaos Strikos, Georgios Keramidas, Stefanos Kaxiras

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia GeForce 8800 GTX

November 22, 2011 by hgpu

GPU-based Multi-start Local Search Algorithms

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 280, Optimization, Search

November 22, 2011 by hgpu

Experiences with Achieving Portability across Heterogeneous Architectures

Lukasz G. Szafaryn, Todd Gamblin, Bronis R. de Supinski, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, OpenMP, Performance

November 22, 2011 by hgpu

Online Adaptive Code Generation and Tuning

Ananta Tiwari, Jeffrey K. Hollingsworth

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Tags: Code generation, Computer science, Optimization

November 21, 2011 by hgpu

Issues in Heterogenenous GPU Clusters

Patrick Carpenter, William Symon

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Tags: Computer science, GPU cluster, Heterogeneous systems, Review

November 21, 2011 by hgpu

A new approach for sparse matrix vector product on NVIDIA GPUs

F. Vazquez, J. J. Fernandez, E. M. Garzon

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Optimization, Sparse matrix

November 21, 2011 by hgpu

Efficient GPGPU-based parallel packet classification

Che-Lun Hung, Yaw-Ling Lin, Kuan-Ching Li, Hsiao-Hsi Wang, Shih-Wei Guo

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Tags: Algorithms, Computer science, CUDA, Filtering, Network communications, nVidia, nVidia GeForce GTS 450, Security

November 21, 2011 by hgpu

Conflux: Embedding Massively Parallel Semantics in a High-Level Programming Language

Eugene Burmako, Rauf Sadykhov

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Tags: Algorithms, Computer science, CUDA, High-level Languages, nVidia, Package

November 21, 2011 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Building-Blocks for Performance Oriented DSLs

TEG: GPU Performance Estimation Using a Timing Model

Dynamic adaptation and distribution of binaries to heterogeneous architectures

Dynamic Heterogeneous Scheduling Decisions Using Historical Runtime Data

Parallelizing Multicore Cache Simulations using Heterogeneous Computing on General Purpose and Graphics Processors

GPU-based Multi-start Local Search Algorithms

Experiences with Achieving Portability across Heterogeneous Architectures

Online Adaptive Code Generation and Tuning

Issues in Heterogenenous GPU Clusters

A new approach for sparse matrix vector product on NVIDIA GPUs

Efficient GPGPU-based parallel packet classification

Conflux: Embedding Massively Parallel Semantics in a High-Level Programming Language

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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