high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

Yuxin Wang, Qiang Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Kaiyong Zhao, Xiaowen Chu

View

Tags: AI, AMD Radeon R7, ATI, Computer science, Deep learning, Neural networks, nVidia, PyTorch, TensorFlow, Tesla P100, Tesla V100, TPU

September 22, 2019 by hgpu

ALPyNA: Acceleration of Loops in Python for Novel Architectures

Dejice Jacob, Jeremy Singer

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 1060, Python

September 22, 2019 by hgpu

Espresso: A Fast End-to-end Neural Speech Recognition Toolkit

Yiming Wang, Tongfei Chen, Hainan Xu, Shuoyang Ding, Hang Lv, Yiwen Shao, Nanyun Peng, Lei Xie, Shinji Watanabe, Sanjeev Khudanpur

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Package, Speech recognition

September 22, 2019 by hgpu

Code optimization based on source to source transformations using profile guided metrics

Youenn Lebras

View

Download (PDF)

Tags: Code generation, Computer science, Performance, Thesis

September 15, 2019 by hgpu

Parallelizing Multiple Flow Accumulation Algorithm using CUDA and OpenACC

Natalija Stojanovic, Dragan Stojanovic

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, OpenACC, Package, Tesla K80

September 15, 2019 by hgpu

Characterizing and Predicting Scientific Workloads for Heterogeneous Computing Systems

Beau Johnston

View

Download (PDF)

Source codes

Tags: Algorithms, AMD Radeon RX 480, ATI Radeon HD 7970, Benchmarking, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, Tesla K20, Tesla K40, Thesis

September 15, 2019 by hgpu

Efficient Interleaved Batch Matrix Solvers for CUDA

Andrew Gloster, Enda Carroll, Miguel Bustamante, Lennon O'Naraigh

View

Download (PDF)

Source codes

Tags: Algorithms, Computational Physics, Computer science, CUDA, Matrix inversion, nVidia, Package, Tesla V100

September 15, 2019 by hgpu

ArborX: A Performance Portable Search Library

D. Lebrun-Grandie, A. Prokopenko, B. Turcksin, S. R. Slattery

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Mathematical Software, MPI, OpenMP, Package, performance portability

September 8, 2019 by hgpu

Fast Code Exploration for Pipeline Processing in FPGA Accelerators

Leandro de Souza Rosa

View

Download (PDF)

Tags: Computer science, Design space exploration, FPGA, HLS, Thesis

September 8, 2019 by hgpu

FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

Xuezhe Ma, Chunting Zhou, Xian Li, Graham Neubig, Eduard Hovy

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, NLP, nVidia, nVidia GeForce GTX Titan X, Package

September 8, 2019 by hgpu

Compilers for Portable Programming of Heterogeneous Parallel & Approximate Computing Systems

Prakalp Srivastava

View

Download (PDF)

Tags: Code generation, Computer science, Design space exploration, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, performance portability

September 8, 2019 by hgpu

Neural Network Inference on Mobile SoCs

Siqi Wang, Anuj Pathania, Tulika Mitra

View

Download (PDF)

Tags: ARM, Computer science, Heterogeneous systems, Machine learning, Neural networks, SoC

September 8, 2019 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Performance and Power Evaluation of AI Accelerators for Training Deep Learning Models

ALPyNA: Acceleration of Loops in Python for Novel Architectures

Espresso: A Fast End-to-end Neural Speech Recognition Toolkit

Code optimization based on source to source transformations using profile guided metrics

Parallelizing Multiple Flow Accumulation Algorithm using CUDA and OpenACC

Characterizing and Predicting Scientific Workloads for Heterogeneous Computing Systems

Efficient Interleaved Batch Matrix Solvers for CUDA

ArborX: A Performance Portable Search Library

Fast Code Exploration for Pipeline Processing in FPGA Accelerators

FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

Compilers for Portable Programming of Heterogeneous Parallel & Approximate Computing Systems

Neural Network Inference on Mobile SoCs

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Most viewed papers (last 30 days)