research
∙
06/28/2023
FuzzyFlow: Leveraging Dataflow To Find and Squash Program Optimization Bugs
The current hardware landscape and application scale is driving performa...
share
research
∙
06/16/2022
Deinsum: Practically I/O Optimal Multilinear Algebra
Multilinear algebra kernel performance on modern massively-parallel syst...
research
∙
04/13/2022
Fast Arbitrary Precision Floating Point on FPGA
Numerical codes that require arbitrary precision floating point (APFP) n...
research
∙
08/20/2021
On the Parallel I/O Optimality of Linear Algebra Kernels: Near-Optimal Matrix Factorizations
Matrix factorizations are among the most important building blocks of sc...
research
∙
07/01/2021
Productivity, Portability, Performance: Data-Centric Python
Python has become the de facto language for scientific computing. Progra...
research
∙
05/15/2021
Pebbles, Graphs, and a Pinch of Combinatorics: Towards Tight I/O Lower Bounds for Statically Analyzable Programs
Determining I/O lower bounds is a crucial step in obtaining communicatio...
research
∙
10/12/2020
On the Parallel I/O Optimality of Linear Algebra Kernels: Near-Optimal LU Factorization
Dense linear algebra kernels, such as linear solvers or tensor contracti...
research
∙
12/18/2019
Optimizing the Data Movement in Quantum Transport Simulations via Data-Centric Parallel Programming
Designing efficient cooling systems for integrated circuits (ICs) relies...
research
∙
12/18/2019
A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations
The computational efficiency of a state of the art ab initio quantum tra...
research
∙
02/27/2019
Stateful Dataflow Multigraphs: A Data-Centric Model for Performance Portability on Heterogeneous Architectures
The ubiquity of accelerators in high-performance computing has driven pr...
research
∙
02/27/2019
Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs
With the ubiquity of accelerators, such as FPGAs and GPUs, the complexit...
research
∙
01/29/2019
