high performance computing on graphics processing units: hgpu.org

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Non-deterministic parallelism considered useful

Derek G. Murray, Steven Hand

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Tags: Computer science, Programming techniques

September 21, 2011 by hgpu

Parallel graduated assignment algorithm for multiple graph matching based on a common labelling

David Rodenas, Francesc Serratosa, Albert Sole-Ribalta

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia ION, Presentation

September 21, 2011 by hgpu

GPU-based cloud performance for LiDAR data processing

Ramanathan Sugumaran, Dossay Oryspayev, Paul Gray

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Tags: Algorithms, Cloud, Computer science, CUDA, Data mining, Databases, Earth and Space Sciences, nVidia, Performance

September 21, 2011 by hgpu

Multicore performance optimization using partner cores

Eric Lau, Jason E. Miller, Inseok Choi, Donald Yeung, Saman Amarasinghe, Anant Agarwal

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Tags: Computer science, Optimization, Programming techniques

September 21, 2011 by hgpu

Mint: realizing CUDA performance in 3D stencil methods with annotated C

Didem Unat, Xing Cai, Scott B. Baden

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Source codes

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenMP, Optimization, Package, Performance, Programming Languages, Tesla C1060

September 21, 2011 by hgpu

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

Ashwin Prasad, Jayvant Anantpur, R. Govindarajan

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Tags: Benchmarking, Clustering, Computer science, CUDA, Data parallelism, Flow analysis, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, Optimization

September 20, 2011 by hgpu

Automatic abstraction and fault tolerance in cortical microachitectures

Atif Hashmi, Hugues Berry, Olivier Temam, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Fault simulation, nVidia, nVidia GeForce 9800 GT

September 20, 2011 by hgpu

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

Wing-kei S. Yu, Ruirui Huang, Sarah Q. Xu, Sung-En Wang, Edwin Kan, G. Edward Suh

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Tags: Benchmarking, Computer science, Memory, nVidia, Performance

September 20, 2011 by hgpu

Brief announcement: better speedups for parallel max-flow

George Constantin Caragea, Uzi Vishkin

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Tags: Algorithms, ASIC, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 280, Performance

September 20, 2011 by hgpu

Hermes: an integrated CPU/GPU microarchitecture for IP routing

Yuhao Zhu, Yangdong Deng, Yubei Chen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Software router

September 20, 2011 by hgpu

CuMAPz: a tool to analyze memory access patterns in CUDA

Yooseong Kim, Aviral Shrivastava

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory, nVidia, Performance, Tesla C1060

September 20, 2011 by hgpu

EFFEX: an embedded processor for computer vision based feature extraction

Jason Clemons, Andrew Jones, Robert Perricone, Silvio Savarese, Todd Austin

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 210, nVidia GeForce GTX 260, SIFT

September 20, 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

Non-deterministic parallelism considered useful

Parallel graduated assignment algorithm for multiple graph matching based on a common labelling

Multicore performance optimization using partner cores

Mint: realizing CUDA performance in 3D stencil methods with annotated C

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

Automatic abstraction and fault tolerance in cortical microachitectures

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

Brief announcement: better speedups for parallel max-flow

Hermes: an integrated CPU/GPU microarchitecture for IP routing

CuMAPz: a tool to analyze memory access patterns in CUDA

EFFEX: an embedded processor for computer vision based feature extraction

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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