DeepAI AI Chat
Log In Sign Up

Randomized Algorithms for Scientific Computing (RASC)

by   Aydin Buluc, et al.

Randomized algorithms have propelled advances in artificial intelligence and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. This report summarizes the outcomes of that workshop, "Randomized Algorithms for Scientific Computing (RASC)," held virtually across four days in December 2020 and January 2021.


page 12

page 13

page 15

page 17

page 30

page 31

page 35

page 38


Report of the Workshop on Program Synthesis for Scientific Computing

Program synthesis is an active research field in academia, national labs...

Artificial Intelligence for Social Good

The Computing Community Consortium (CCC), along with the White House Off...

Photonics for artificial intelligence and neuromorphic computing

Research in photonic computing has flourished due to the proliferation o...

Notes on Randomized Algorithms

Lecture notes for the Yale Computer Science course CPSC 469/569 Randomiz...

Towards a Modular Architecture for Science Factories

Advances in robotic automation, high-performance computing (HPC), and ar...

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for...

NSF Convergence Approach to Transition Basic Research into Practice

The National Science Foundation Convergence Accelerator addresses nation...