research
∙
06/06/2023
Exploiting Scratchpad Memory for Deep Temporal Blocking: A case study for 2D Jacobian 5-point iterative stencil kernel (j2d5pt)
General Purpose Graphics Processing Units (GPGPU) are used in most of th...
share
research
∙
05/12/2023
Revisiting Temporal Blocking Stencil Optimizations
Iterative stencils are used widely across the spectrum of High Performan...
research
∙
01/06/2023
Myths and Legends in High-Performance Computing
In this humorous and thought provoking article, we discuss certain myths...
research
∙
08/24/2022
Flash-X, a multiphysics simulation software instrument
Flash-X is a highly composable multiphysics software system that can be ...
research
∙
05/12/2022
Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction
Ptychography is a popular microscopic imaging modality for many scientif...
research
∙
04/15/2022
Preparing for the Future – Rethinking Proxy Apps
A considerable amount of research and engineering went into designing pr...
research
∙
04/05/2022
Persistent Kernels for Iterative Memory-bound GPU Applications
Iterative memory-bound solvers commonly occur in HPC codes. Typical GPU ...
research
∙
10/21/2021
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems
Scientific communities are increasingly adopting machine learning and de...
research
∙
04/27/2021
Performance Portable Back-projection Algorithms on CPUs: Agnostic Data Locality and Vectorization Optimizations
Computed Tomography (CT) is a key 3D imaging technology that fundamental...
research
∙
04/19/2021
An Oracle for Guiding Large-Scale Model/Hybrid Parallel Training of Convolutional Neural Networks
Deep Neural Network (DNN) frameworks use distributed training to enable ...
research
∙
10/27/2020
Matrix Engines for High Performance Computing:A Paragon of Performance or Grasping at Straws?
Matrix engines or units, in different forms and affinities, are becoming...
research
∙
08/26/2020
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA
The dedicated memory of hardware accelerators can be insufficient to sto...
research
∙
08/19/2020
A Computational-Graph Partitioning Method for Training Memory-Constrained DNNs
We propose ParDNN, an automatic, generic, and non-intrusive partitioning...
research
∙
04/11/2020
A Study of Single and Multi-device Synchronization Methods in Nvidia GPUs
GPUs are playing an increasingly important role in general-purpose compu...
research
∙
01/06/2020
AN5D: Automated Stencil Framework for High-Degree Temporal Blocking on GPUs
Stencil computation is one of the most widely-used compute patterns in h...
research
∙
09/06/2019
iFDK: A Scalable Framework for Instant High-resolution Image Reconstruction
Computed Tomography (CT) is a widely used technology that requires compu...
research
∙
07/14/2019
A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels
This paper proposes a versatile high-performance execution model, inspir...
research
∙
10/22/2018
