high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia P100

Data-driven Forecasting of Deep Learning Performance on GPUs

Seonho Lee, Amar Phanishayee, Divya Mahajan

View

Tags: Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia H100, nVidia P100, nVidia V100, Performance, PyTorch, Tesla T4

August 4, 2024 by hgpu

Adapting database components to heterogeneous environments

Dimitrios Koutsoukos

View

Download (PDF)

Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia P100, Thesis

June 30, 2024 by hgpu

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

Martin Karp

View

Download (PDF)

Tags: AMD Radeon Instinct MI250X, ATI, cfd, Fluid dynamics, FPGA, Heterogeneous systems, Numerical simulation, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, Spectral elements, Thesis

May 12, 2024 by hgpu

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis

Shiwei Zhang, Lansong Diao, Chuan Wu, Zongyan Cao, Siyu Wang, Wei Lin

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Distributed computing, GPU cluster, nVidia, nVidia A100, nVidia P100, nVidia V100, Package, PyTorch

January 14, 2024 by hgpu

A Comparison of the Performance of the Molecular Dynamics Simulation Package GROMACS Implemented in the SYCL and CUDA Programming Models

Leonard Apanasevich, Yogesh Kale, Himanshu Sharma, Ana Marija Sokovic

View

Download (PDF)

Tags: Benchmarking, Bioinformatics, Biology, Chemistry, Computer science, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, OpenMP, Performance, SYCL

November 5, 2023 by hgpu

GEVO-ML: Optimizing Machine Learning Code with Evolutionary Computation

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

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia P100

October 29, 2023 by hgpu

Improving Performance of Iterative Applications through Interleaved Execution of Approximated CUDA Kernels

Gabriel Freytag

View

Download (PDF)

Tags: Computer science, CUDA, Machine learning, Mixed precision, Neural networks, nVidia, nVidia A100, nVidia P100, Thesis

June 18, 2023 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Data-driven Forecasting of Deep Learning Performance on GPUs

Adapting database components to heterogeneous environments

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis

A Comparison of the Performance of the Molecular Dynamics Simulation Package GROMACS Implemented in the SYCL and CUDA Programming Models

GEVO-ML: Optimizing Machine Learning Code with Evolutionary Computation

Improving Performance of Iterative Applications through Interleaved Execution of Approximated CUDA Kernels

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

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

Most viewed papers (last 30 days)