Heterogeneous systems | Page 42

hgpu.org » Heterogeneous systems

Modern Gyrokinetic Particle-In-Cell Simulation of Fusion Plasmas on Top Supercomputers

Bei Wang, Stephane Ethier, William Tang, Khaled Ibrahim, Kamesh Madduri, Samuel Williams, Leonid Oliker

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Tags: CUDA, Heterogeneous systems, Intel Xeon Phi, Laplace and Poisson equation, nVidia, Particle-in-cell methods, Physics, Plasma physics, Poisson equation, Tesla K20

October 25, 2015 by hgpu

A linguistic approach to concurrent, distributed, and adaptive programming across heterogeneous platforms

Paul Harvey

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Tags: Computer science, Heterogeneous systems, OpenCL, Thesis

October 22, 2015 by hgpu

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Linnan Wang, Wei Wu, Jianxiong Xiao, Yi Yang

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Source codes

Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K40

October 22, 2015 by hgpu

Implementation of a Power Efficient Synthetic Aperture Radar Back Projection Algorithm on FPGAs Using OpenCL

David Fan

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Tags: Algorithms, FPGA, Heterogeneous systems, nVidia, OpenCL, SAR, Signal processing, Tesla K40, Thesis

October 18, 2015 by hgpu

Performance analysis and optimization of a CFD application

Wentao Zhang

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Tags: Finite difference, Fluid dynamics, Fortran, Heterogeneous systems, Intel Xeon Phi, Performance, Thesis

October 18, 2015 by hgpu

Density-based parallel skin lesion border detection with webCL

James Lemon, Sinan Kockara, Tansel Halic, Mutlu Mete

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Tags: Algorithms, Bioinformatics, Clustering, Heterogeneous systems, Image processing, Java, OpenCL

October 16, 2015 by hgpu

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

Linchuan Chen

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, Matrix multiplication, MPI, nVidia, Sparse matrix, Task scheduling, Tesla M2070, Thesis

October 13, 2015 by hgpu

Accelerating the D3Q19 Lattice Boltzmann Model with OpenACC and MPI

Alessandro Gabbana

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Tags: Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, MPI, nVidia, OpenACC, Tesla K80, Thesis

October 11, 2015 by hgpu

Solving the Quadratic Assignment Problem on heterogeneous environment (CPUs and GPUs) with the application of Level 2 Reformulation and Linearization Technique

Alexandre Domingues Goncalves, Artur Alves Pessoa, Lucia Maria de Assumpcao Drummond, Cristiana Bentes, Ricardo Farias

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, Tesla C2070

October 8, 2015 by hgpu

A Design Framework for Mapping Dataflow Graphs onto Heterogeneous Multiprocessor Platforms

Shuoxin Lin

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Tags: Benchmarking, Computer science, CUDA, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, Thesis

September 29, 2015 by hgpu

Automatic OpenCL code generation for multi-device heterogeneous architectures

Pei Li, Elisabeth Brunet, Francois Trahay, Christian Parrot, Gael Thomas, Raymond Namyst

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Tags: Code generation, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia Quadro FX 5800, OpenCL

September 19, 2015 by hgpu

Autotuning Wavefront Patterns for Heterogeneous Architectures

Siddharth Mohanty

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenCL, Performance, Thesis

September 19, 2015 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

Modern Gyrokinetic Particle-In-Cell Simulation of Fusion Plasmas on Top Supercomputers

A linguistic approach to concurrent, distributed, and adaptive programming across heterogeneous platforms

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Implementation of a Power Efficient Synthetic Aperture Radar Back Projection Algorithm on FPGAs Using OpenCL

Performance analysis and optimization of a CFD application

Density-based parallel skin lesion border detection with webCL

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

Accelerating the D3Q19 Lattice Boltzmann Model with OpenACC and MPI

Solving the Quadratic Assignment Problem on heterogeneous environment (CPUs and GPUs) with the application of Level 2 Reformulation and Linearization Technique

A Design Framework for Mapping Dataflow Graphs onto Heterogeneous Multiprocessor Platforms

Automatic OpenCL code generation for multi-device heterogeneous architectures

Autotuning Wavefront Patterns for Heterogeneous Architectures

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

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