high performance computing on graphics processing units: hgpu.org

Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Meghan Cowan, Haichen Shen, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

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Tags: Compilers, Computer science, Deep learning, FPGA, Machine learning, nVidia, nVidia GeForce GTX Titan X, Optimization, Package, performance portability

October 13, 2018 by hgpu

Mass_Flow_Estimation: Semi-supervised implementation of a DNN for mass prediction from sparsely labeled images

Mass Estimation from Images using Deep Neural Network and Sparse Ground Truth

KNN: k-Nearest Neighbours algorithm

High Performance Computing via High Level Synthesis

SODECL: library of ordinary differential equation (ODE) and stochastic differential equation (SDE) solvers in OpenCL

SODECL: An Open Source Library for Calculating Multiple Orbits of a System of Stochastic Differential Equations in Parallel

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2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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high performance computing on graphics processing units: hgpu.org

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

Automatic generation of warp-level primitives and atomic instructions for fast and portable parallel reduction on GPUs

Principles, Techniques, and Tools for Explicit and Automatic Parallelization

Cross-Platform Performance Portability Using Highly Parametrized SYCL Kernels

On the Portability of GPU-Accelerated Applications via Automated Source-to-Source Translation

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation

Heterogeneous Distributed Big Data Clustering on Sparse Grids

Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

Delivering Performance-Portable Stencil Computations on CPUs and GPUs Using Bricks

Performance Portability Challenges for Fortran Applications

OpenCL Performance Prediction using Architecture-Independent Features

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

Recent source codes

Mass_Flow_Estimation: Semi-supervised implementation of a DNN for mass prediction from sparsely labeled images

KNN: k-Nearest Neighbours algorithm

SODECL: library of ordinary differential equation (ODE) and stochastic differential equation (SDE) solvers in OpenCL

sisph: Simple Iterative Incompressible Smoothed Particle Hydrodynamics

GraphBLAST: High-Performance Linear Algebra-based Graph Primitives on GPUs

FAST: Framework for Heterogeneous Medical Image Computing and Visualization

ESBMC-GPU

FBLAS: BLAS implementation for Intel FPGA

CuLE: A CUDA port of the Atari Learning Environment (ALE)

MagmaDNN

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Featured events

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019