high performance computing on graphics processing units: hgpu.org

Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett Phillips, Ankur Mahesh, Michael Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston

View

Download (PDF)

Tags: CUDA, Deep learning, Earth and Space Sciences, Neural networks, nVidia, TensorFlow, Tesla V100, Weather prediction

October 6, 2018 by hgpu

Evaluating Performance Portability of Accelerator Programming Models using SPEC ACCEL 1.2 Benchmarks

Swen Boehm, Swaroop Pophale, Veronica G. Vergara Larrea, Oscar Hernandez

View

Download (PDF)

Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenACC, OpenCL, OpenMP, performance portability, Tesla K20, Tesla V100

September 23, 2018 by hgpu

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Jianyu Huang, Chenhan D. Yu, Robert A. van de Geijn

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Package, Tesla V100

September 2, 2018 by hgpu

Full Speed Ahead: 3D Spatial Database Acceleration with GPUs

Lucas C. Villa Real, Bruno Silva

View

Download (PDF)

Tags: Computer science, CUDA, Databases, nVidia, Tesla V100

September 2, 2018 by hgpu

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Raul Puri, Robert Kirby, Nikolai Yakovenko, Bryan Catanzaro

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, LSTM, Mixed precision, Neural networks, nVidia, Package, Tesla V100, Torch

August 11, 2018 by hgpu

XGBoost: Scalable GPU Accelerated Learning

Rory Mitchell, Andrey Adinets, Thejaswi Rao, Eibe Frank

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Java, Machine learning, nVidia, Package, Python, R, Scala, Tesla V100

July 5, 2018 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

BitCracker: BitLocker meets GPUs

wav2letter++: The Fastest Open-source Speech Recognition System

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience

Performance Portability Challenges for Fortran Applications

Modeling Deep Learning Accelerator Enabled GPUs

The AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data with GPUs

Exascale Deep Learning for Climate Analytics

Evaluating Performance Portability of Accelerator Programming Models using SPEC ACCEL 1.2 Benchmarks

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Full Speed Ahead: 3D Spatial Database Acceleration with GPUs

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

XGBoost: Scalable GPU Accelerated Learning

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)