high performance computing on graphics processing units: hgpu.org

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Heterogeneous Computing for Solving System of the Linear Equations by the Conjugate Gradient Method

Eduard Bondarenko

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Tags: Computer science, Conjugate gradient solver, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 650 Ti, OpenACC

May 29, 2014 by hgpu

A Parallel Jacobi-Type Lattice Basis Reduction Algorithm

Filip Jeremic, Sanzheng Qiao

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 660

May 26, 2014 by hgpu

A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU

Tingxing Dong, Veselin Dobrev, Tzanio Kolev, Robert Rieben, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, CUDA, FEM, Finite element method, Linear Algebra, nVidia, Tesla K20

May 20, 2014 by hgpu

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Jakub Kurzak, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680

May 14, 2014 by hgpu

Analysis of SuperLU Solvers on Intel MIC Architecture

Ahmet Duran, M. Serdar Celebi, Bora Akaydin, Mehmet Tuncel, Figen Oztoprak

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Tags: Computer science, Intel Xeon Phi, Linear Algebra, Sparse matrix

May 2, 2014 by hgpu

Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures

Hartwig Anzt, Dimitar Lukarski, Stanimire Tomov, Jack Dongarra

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, Tesla K40

April 27, 2014 by hgpu

Integrating multi-threading and accelerators into DUNE-ISTL

Steffen Muthing, Dirk Ribbrock, Dominik Goddeke

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Partial differential equations, PDEs, Tesla C2070

April 25, 2014 by hgpu

Galerkin-based multi-scale time integration for nonlinear structural dynamics

Matthias Bartelt, Michael Gross

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Tags: CUDA, Differential equations, Linear Algebra, Mathematics, Numerical simulation, nVidia, ODEs, Ordinary differential equations, Partial differential equations, PDEs, Tesla C2075

April 24, 2014 by hgpu

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Luka Stanisic, Samuel Thibault, Arnaud Legrand, Brice Videau, Jean-Francois Mehaut

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Performance, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075

April 9, 2014 by hgpu

Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs

Hartwig Anzt, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Sorting, Sparse matrix, Tesla K40

April 7, 2014 by hgpu

Optimizing Krylov Subspace Solvers on Graphics Processing Units

Hartwig Anzt, Stanimire Tomov, Piotr Luszczek, Ichitaro Yamazaki, Jack Dongarra, William Sawyer

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Sparse matrix, Tesla K20

April 6, 2014 by hgpu

Parallel Support Vector Machines in Practice

Stephen Tyree, Jacob R. Gardner, Kilian Q. Weinberger, Kunal Agrawal, John Tran

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, Package, Tesla C2075

April 6, 2014 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Heterogeneous Computing for Solving System of the Linear Equations by the Conjugate Gradient Method

A Parallel Jacobi-Type Lattice Basis Reduction Algorithm

A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Analysis of SuperLU Solvers on Intel MIC Architecture

Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures

Integrating multi-threading and accelerators into DUNE-ISTL

Galerkin-based multi-scale time integration for nonlinear structural dynamics

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-sigma formats on NVIDIA GPUs

Optimizing Krylov Subspace Solvers on Graphics Processing Units

Parallel Support Vector Machines in Practice

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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