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On the design of sparse hybrid linear solvers for modern parallel architectures

Stojce Nakov

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Sparse linear iterative solvers, Sparse matrix, Tesla K40, Tesla M2070, Thesis

April 29, 2016 by hgpu

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Alcides Fonseca, Bruno Cabral, Joao Rafael, Ivo Correia

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Tags: Computer science, Java, OpenCL, Package, Programming Languages

April 29, 2016 by hgpu

Adaptive GPU Array Layout Auto-Tuning

Nicolas Weber, Michael Goesele

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Tags: Computer science, CUDA, Linear Algbera, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K20

April 29, 2016 by hgpu

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

Nilothpal Talukder

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, MPI, nVidia, Tesla C2075, Thesis

April 29, 2016 by hgpu

GPU-Aware Non-contiguous Data Movement In Open MPI

Wei Wu, George Bosilca, Rolf vandeVaart, Sylvain Jeaugey, Jack Dongarra

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Tags: Computer science, CUDA, MPI, nVidia, Tesla K40

April 26, 2016 by hgpu

Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures

Benjamin Worpitz

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Tags: Computer science, CUDA, Intel Xeon Phi, OpenMP, Package, Particle-in-cell methods, Performance, performance portability, Tesla K20, Tesla K80, Thesis

April 26, 2016 by hgpu

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

Feng Zhang, Jidong Zhai, Wenguang Chen, Bingsheng He, Shuhao Zhang

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Tags: Benchmarking, Computer science, OpenCL, Package

April 26, 2016 by hgpu

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

Ilya Loshchilov, Frank Hutter

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Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Python

April 26, 2016 by hgpu

GPL: A GPU-based Pipelined Query Processing Engine

Johns Paul, Jiong He, Bingsheng He

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Tags: Analytical model, Computer science, Databases, nVidia, OpenCL

April 24, 2016 by hgpu

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

M. Abalenkovs, A. Abdelfattah, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, I. Yamazaki, A. YarKhan

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Programming techniques, Review, Tesla K40

April 19, 2016 by hgpu

A Parallel Solution to Finding Nodal Neighbors in Generic Meshes

Gang Mei, Nengxiong Xu, Hong Tian

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Tags: Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GT 640

April 19, 2016 by hgpu

MIML Learning with CNNs: Yelp Restaurant Photo Classification

Pulkit Agrawal, Raghav Gupta

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Tags: CNN, Computer science, CUDA, Deep learning, Intel Xeon Phi, nVidia

April 19, 2016 by hgpu

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

OpScanner

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

Enhancing Transformer Performance and Portability through Auto-tuning Frameworks

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high performance computing on graphics processing units: hgpu.org

On the design of sparse hybrid linear solvers for modern parallel architectures

Automatic Parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

Adaptive GPU Array Layout Auto-Tuning

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

GPU-Aware Non-contiguous Data Movement In Open MPI

Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures

To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

GPL: A GPU-based Pipelined Query Processing Engine

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

A Parallel Solution to Finding Nodal Neighbors in Generic Meshes

MIML Learning with CNNs: Yelp Restaurant Photo Classification

Recent source codes

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

pplx-garden: Perplexity open source garden for inference technology

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

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