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On the Effectiveness of OpenMP teams for Programming Embedded Manycore Accelerators

Alessandro Capotondi, Andrea Marongiu

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Tags: Computer science, Heterogeneous systems, OpenMP, Performance, SoC

November 8, 2015 by hgpu

Data Stream Classification using Random Feature Functions and Novel Method Combinations

Diego Marron, Jesse Read, Albert Bifet, Nacho Navarro

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Tags: Computer science, CUDA, Deep learning, Nearest neighbour, Neural networks, nVidia, Tesla K40

November 8, 2015 by hgpu

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Vincenzo Lomonaco

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Pattern recognition, Tesla C2075, Thesis

November 8, 2015 by hgpu

Efficient Sparse Matrix-Vector Multiplication on GPUs using the CSR Storage Format

Joseph L. Greathouse, Mayank Daga

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Tags: Algorithms, AMD FirePro W9100, ATI, Computer science, Linear Algebra, OpenCL, Sparse matrix

November 4, 2015 by hgpu

Performance of GTX Titan X GPUs and Code Optimization

Hwancheol Jeong, Sangbaek Lee, Weonjong Lee, Jeonghwan Pak, Jangho Kim, Juhyun Chung

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, Performance

November 4, 2015 by hgpu

Heterogeneous CPU/(GP) GPU Memory Hierarchy Analysis and Optimization

Josue Vladimir Quiroga Esparza

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, Thesis

November 4, 2015 by hgpu

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

Hector Dearman

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Tags: Benchmarking, Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, nVidia GRID K520, OpenCL, Partial differential equations, PDEs, Thesis

November 3, 2015 by hgpu

A Framework for Transparent Execution of Massively-Parallel Applications on CUDA and OpenCL

Jorn Teuber, Rene Weller, Gabriel Zachmann

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenCL

November 3, 2015 by hgpu

Structural Agnostic SpMV: Adapting CSR-Adaptive for Irregular Matrices

Mayank Daga, Joseph L. Greathouse

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Source codes

Tags: Algorithms, AMD FirePro W9100, APU, ATI, Computer science, Linear Algebra, OpenCL, Package, Sparse matrix

November 3, 2015 by hgpu

On the programmability of multi-GPU computing systems

Javier Cabezas Rodriguez

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Tesla C1060, Tesla K20, Tesla K40, Thesis

November 3, 2015 by hgpu

Energy-Efficient Execution of Data-Parallel Applications on Heterogeneous Mobile Platforms

Alok Prakash, Siqi Wang, Alexandru Eugen Irimiea, Tulika Mitra

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Tags: ARM, Computer science, Heterogeneous systems, OpenCL, SoC

October 31, 2015 by hgpu

Estimation of numerical reproducibility on CPU and GPU

Fabienne Jezequel, Jean-Luc Lamotte, Issam Said

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, OpenCL, Tesla C2050, Tesla K20

October 31, 2015 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

On the Effectiveness of OpenMP teams for Programming Embedded Manycore Accelerators

Data Stream Classification using Random Feature Functions and Novel Method Combinations

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Efficient Sparse Matrix-Vector Multiplication on GPUs using the CSR Storage Format

Performance of GTX Titan X GPUs and Code Optimization

Heterogeneous CPU/(GP) GPU Memory Hierarchy Analysis and Optimization

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

A Framework for Transparent Execution of Massively-Parallel Applications on CUDA and OpenCL

Structural Agnostic SpMV: Adapting CSR-Adaptive for Irregular Matrices

On the programmability of multi-GPU computing systems

Energy-Efficient Execution of Data-Parallel Applications on Heterogeneous Mobile Platforms

Estimation of numerical reproducibility on CPU and GPU

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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