high performance computing on graphics processing units: hgpu.org

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Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Varun Nagpal

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C1060, Thesis

March 10, 2016 by hgpu

Enhancing productivity and performance portability of OpenCL applications on heterogeneous systems using runtime optimizations

Thibaut Lutz

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Tags: Computer science, nVidia, nVidia GeForce GTX 780, OpenCL, Performance, performance portability, PTX, Thesis

March 8, 2016 by hgpu

Compiler and runtime techniques for bulk-synchronous programming models on CPU architectures

Hee-Seok Kim

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Tags: Compilers, Computer science, OpenCL, performance portability, Thesis

March 8, 2016 by hgpu

A Novel Mapping of Arbitrary Precision Integer Operations to the GPU

Matthias Gusenbauer

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Tags: Computer science, nVidia, nVidia GeForce GTX Titan X, OpenCL, Thesis

March 8, 2016 by hgpu

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Sriram Kankatala

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Tags: Computer science, CUDA, Data mining, Databases, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 550 Ti, Pattern recognition, Pthreads, Thesis

March 5, 2016 by hgpu

Heterogeneous parallel algorithms for Computational Fluid Dynamics on unstructured meshes

Guillermo Andres Oyarzun Altamirano

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Tags: cfd, CUDA, Fluid dynamics, MPI, nVidia, OpenCL, SoC, Tesla M2090, Thesis

March 5, 2016 by hgpu

Optimization of Molecular Dynamics Simulation Code and Applications to Biomolecular Systems

David M. Bowman

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Tags: Biochemistry, Biomolecules, Chemistry, CUDA, Molecular dynamics, MPI, nVidia, OpenCL, OpenMP, Thesis

March 1, 2016 by hgpu

Parallel Approaches to Shortest-Path Problems for Multilevel Heterogeneous Computing

Hector Ortega Arranz

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Path problems, Thesis

February 25, 2016 by hgpu

Sparse Convex Optimization on GPUs

Marco Maggioni

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla K40, Thesis

February 23, 2016 by hgpu

Speeding Up Reinforcement Learning with Graphics Processing Units

Jorn H. Postma

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Tags: Algorithms, Computer science, KD-tree, Machine learning, nVidia, OpenCL, Tesla C2075, Thesis

February 18, 2016 by hgpu

Finding, Measuring, and Reducing Inefficiencies in Contemporary Computer Systems

Melanie Rae Kambadur

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Source codes

Tags: Computer science, Intel HD 4600, Intel HD Graphics 4000, LLVM, OpenCL, Package, Performance, Thesis

February 16, 2016 by hgpu

Towards Improving Programmability of Heterogeneous Parallel Architectures

Michele Scandale

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Tags: Compilers, Computer science, Heterogeneous systems, LLVM, OpenCL, Thesis

February 16, 2016 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

See all packages

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high performance computing on graphics processing units: hgpu.org

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Enhancing productivity and performance portability of OpenCL applications on heterogeneous systems using runtime optimizations

Compiler and runtime techniques for bulk-synchronous programming models on CPU architectures

A Novel Mapping of Arbitrary Precision Integer Operations to the GPU

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Heterogeneous parallel algorithms for Computational Fluid Dynamics on unstructured meshes

Optimization of Molecular Dynamics Simulation Code and Applications to Biomolecular Systems

Parallel Approaches to Shortest-Path Problems for Multilevel Heterogeneous Computing

Sparse Convex Optimization on GPUs

Speeding Up Reinforcement Learning with Graphics Processing Units

Finding, Measuring, and Reducing Inefficiencies in Contemporary Computer Systems

Towards Improving Programmability of Heterogeneous Parallel Architectures

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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