high performance computing on graphics processing units: hgpu.org

Xiaojue Zhu, Everett Phillips, Vamsi Spandan, John Donners, Gregory Ruetsch, Josh Romero, Rodolfo Ostilla-Monico, Yantao Yang, Detlef Lohse, Roberto Verzicco, Massimiliano Fatica, Richard J.A.M. Stevens

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Tags: cfd, CUDA, Fluid dynamics, Fortran, GPU cluster, MPI, Navier-Stokes equations, NSEs, nVidia, Package, Tesla K20, Tesla P100, Tesla T40

May 6, 2017 by hgpu

TinyDL: Just-In-Time Deep Learning Solution For Constrained Embedded Systems

Bita Darvish Rouhani, Azalia Mirhoseini, Farinaz Koushanfar

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Tags: ARM, Computer science, CUDA, Deep learning, nVidia, nVidia Jetson TK1, Performance

May 2, 2017 by hgpu

Speeding up a few orders of magnitude the Jacobi method: high order Chebyshev-Jacobi over GPUs

J.E. Adsuara, I. Cordero-Carrion, P. Cerda-Duran, M.A. Aloy

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Tags: CUDA, Differential equations, Finite difference, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, Partial differential equations, PDEs, Tesla K40

May 2, 2017 by hgpu

Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

Bin Chen, Ronald Kantowski, Xinyu Dai, Eddie Baron, Paul Van der Mark

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Tags: Astrophysics, CUDA, Gravitation, Gravitational lensing, Intel Xeon Phi, nVidia, OpenMP, Tesla M2050

May 2, 2017 by hgpu

GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Michail Alvanos, Theodoros Christoudias

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Tags: Chemistry, Code generation, CUDA, Earth and Space Sciences, Fortran, nVidia, Package, Tesla M2070

May 2, 2017 by hgpu

Deep Learning in the Automotive Industry: Applications and Tools

Andre Luckow, Matthew Cook, Nathan Ashcraft, Edwin Weill, Emil Djerekarov, Bennie Vorster

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Tags: Cloud, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia GRID K520, Performance

May 2, 2017 by hgpu

Adaptive Optimization for OpenCL Programs on Embedded Heterogeneous Systems

Ben Taylor, Vicent Sanz Marco, Zheng Wang

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Tags: ARM, Computer science, Energy-efficient computing, Heterogeneous systems, Machine learning, OpenCL

April 30, 2017 by hgpu

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

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

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

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high performance computing on graphics processing units: hgpu.org

Applications

Multidimensional upwind hydrodynamics on unstructured meshes using Graphics Processing Units I. Two-dimensional uniform meshes

Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks

cuTT: A High-Performance Tensor Transpose Library for CUDA Compatible GPUs

Numerical Model of Shallow Water: the Use of NVIDIA CUDA Graphics Processors

GPUQT: An efficient linear-scaling quantum transport code fully implemented on graphics processing units

AFiD-GPU: a versatile Navier-Stokes Solver for Wall-Bounded Turbulent Flows on GPU Clusters

TinyDL: Just-In-Time Deep Learning Solution For Constrained Embedded Systems

Speeding up a few orders of magnitude the Jacobi method: high order Chebyshev-Jacobi over GPUs

Accelerating gravitational microlensing simulations using the Xeon Phi coprocessor

GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Adaptive Optimization for OpenCL Programs on Embedded Heterogeneous Systems

Recent source codes

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

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

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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