high performance computing on graphics processing units: hgpu.org

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Reducing branch divergence in GPU programs

Tianyi David Han, Tarek S. Abdelrahman

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Programming Languages

September 22, 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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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenMP, Optimization, Package, Performance, Programming Languages, Tesla C1060

September 21, 2011 by hgpu

Returning control to the programmer: SIMD intrinsics for virtual machines

Jonathan Parri, Daniel Shapiro, Miodrag Bolic, Voicu Groza

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Tags: Computer science, Java, Optimization, Programming Languages

September 16, 2011 by hgpu

A platform-independent tool for modeling parallel programs

Ferosh Jacob, Jeff Gray, Yu Sun, Purushotham Bangalore

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Tags: Algorithms, Computer science, MPI, OpenMP, Performance, Programming Languages, Programming techniques

September 15, 2011 by hgpu

Nikola: embedding compiled GPU functions in Haskell

Geoffrey Mainland, Greg Morrisett

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Programming Languages, Tesla T10

September 14, 2011 by hgpu

AnySL: efficient and portable shading for ray tracing

Ralf Karrenberg, Dmitri Rubinstein, Philipp Slusallek, Sebastian Hack

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Tags: 3D Graphics and Realism, Code generation, Compilers, Computer science, nVidia, Package, Programming Languages, PTX, Raytracing, Rendering

September 13, 2011 by hgpu

Optimizing a shared virtual memory system for a heterogeneous CPU-accelerator platform

Shoumeng Yan, Xiaocheng Zhou, Ying Gao, Hu Chen, Gansha Wu, Sai Luo, Bratin Saha

Tags: Computer science, Heterogeneous systems, Memory, Operating systems, Performance, Programming Languages

September 12, 2011 by hgpu

Lightweight modular staging: a pragmatic approach to runtime code generation and compiled DSLs

Tiark Rompf, Martin Odersky

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Tags: Code generation, Computer science, Optimization, Programming Languages, Software Engineering

September 11, 2011 by hgpu

The architecture of the DecentVM: towards a decentralized virtual machine for many-core computing

Annette Bieniusa, Johannes Eickhold, Thomas Fuhrmann

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Tags: Computer science, Distributed data structures, Memory model, Programming Languages, Programming techniques

September 9, 2011 by hgpu

MacroSS: macro-SIMDization of streaming applications

Amir H. Hormati, Yoonseo Choi, Mark Woh, Manjunath Kudlur, Rodric Rabbah, Trevor Mudge, Scott Mahlke

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Tags: Code generation, Compilers, Computer science, Optimization, Performance, Programming Languages

September 7, 2011 by hgpu

Bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+

V. Aggarwal, A. George, K. Yalamanchili, C. Yoon, H. Lam, G. Stitt

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Tags: Computer science, FPGA, Heterogeneous systems, Performance, Programming Languages, Programming techniques

September 6, 2011 by hgpu

Exposing non-standard architectures to embedded software using compile-time virtualisation

Ian Gray, Neil C. Audsley

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Tags: Computer science, FPGA, Performance, Programming Languages, Virtualization

August 28, 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

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

BoltzGen:Toward Universal Binder Design

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

Reducing branch divergence in GPU programs

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

Returning control to the programmer: SIMD intrinsics for virtual machines

A platform-independent tool for modeling parallel programs

Nikola: embedding compiled GPU functions in Haskell

AnySL: efficient and portable shading for ray tracing

Optimizing a shared virtual memory system for a heterogeneous CPU-accelerator platform

Lightweight modular staging: a pragmatic approach to runtime code generation and compiled DSLs

The architecture of the DecentVM: towards a decentralized virtual machine for many-core computing

MacroSS: macro-SIMDization of streaming applications

Bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+

Exposing non-standard architectures to embedded software using compile-time virtualisation

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

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

BoltzGen:Toward Universal Binder Design

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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