high performance computing on graphics processing units: hgpu.org

hgpu.org » Machine learning

Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning

Weile Jia, Han Wang, Mohan Chen, Denghui Lu, Jiduan Liu, Lin Lin, Roberto Car, Weinan E, Linfeng Zhang

View

Tags: Computational Physics, CUDA, HPC, Machine learning, Mixed precision, Molecular dynamics, Molecular simulation, MPI, nVidia, OpenMP, Physics, Tesla V100

May 10, 2020 by hgpu

GEVO: GPU Code Optimization using Evolutionary Computation

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, Package, PTX, Tesla P100

April 26, 2020 by hgpu

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

Tsung-Wei Huang, Dian-Lun Lin, Yibo Lin, Chun-Xun Lin

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, Package, Performance

April 26, 2020 by hgpu

FlexTensor: An Automatic Schedule Exploration and Optimization Framework for Tensor Computation on Heterogeneous System

Size Zheng, Yun Liang, Shuo Wang, Renze Chen, Kaiwen Sheng

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, FPGA, Heterogeneous systems, Machine learning, nVidia, OpenCL, Package, Tesla V100

April 19, 2020 by hgpu

Using Machine Learning to Estimate Utilization and Throughput for OpenCL-Based SpMV Implementation on an FPGA

Jannatun Naher, Clay Gloster, Shrikant S. Jadhav, Christopher C. Doss

View

Download (PDF)

Tags: Computer science, Design space exploration, DSP, FPGA, Linear Algebra, Machine learning, OpenCL, Sparse matrix

April 12, 2020 by hgpu

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Hugh Leather

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 970, OpenCL, Package, Performance, Programming Languages

March 29, 2020 by hgpu

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Peng Zhang, Jianbin Fang, Canqun Yang, Chun Huang, Tao Tang, Zheng Wang

View

Download (PDF)

Source codes

Tags: Analytical model, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, Machine learning, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, OpenMP, Package

March 22, 2020 by hgpu

Learnergy: Energy-based Machine Learners

Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Energy-efficient computing, Machine learning, Neural networks, nVidia, Package, Python, PyTorch

March 22, 2020 by hgpu

Towards automated kernel selection in machine learning systems: A SYCL case study

John Lawson

View

Download (PDF)

Source codes

Tags: AMD R9 Nano, ATI, Computer science, Heterogeneous systems, Machine learning, Package, Performance, SYCL

March 22, 2020 by hgpu

The Deep Learning Compiler: A Comprehensive Survey

Mingzhen Li, Yi Liu, Xiaoyan Liu, Qingxiao Sun, Xin You, Hailong Yang, Zhongzhi Luan, Depei Qian

View

Download (PDF)

Tags: Compilers, Computer science, Deep learning, Machine learning, Performance

February 16, 2020 by hgpu

TC-CIM: Empowering Tensor Comprehensions for Computing-In-Memory

Andi Drebes, Lorenzo Chelini, Oleksandr Zinenko, Albert Cohen, Henk Corporaal, Tobias Grosser, Kanishkan Vadivel, Nicolas Vasilache

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, Machine learning

February 9, 2020 by hgpu

Non-Determinism in TensorFlow ResNets

Miguel Morin, Matthew Willetts

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, Machine learning, nVidia, Package, TensorFlow, Tesla M60

February 2, 2020 by hgpu

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

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning

GEVO: GPU Code Optimization using Evolutionary Computation

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

FlexTensor: An Automatic Schedule Exploration and Optimization Framework for Tensor Computation on Heterogeneous System

Using Machine Learning to Estimate Utilization and Throughput for OpenCL-Based SpMV Implementation on an FPGA

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Learnergy: Energy-based Machine Learners

Towards automated kernel selection in machine learning systems: A SYCL case study

The Deep Learning Compiler: A Comprehensive Survey

TC-CIM: Empowering Tensor Comprehensions for Computing-In-Memory

Non-Determinism in TensorFlow ResNets

Recent source codes

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

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

Most viewed papers (last 30 days)