YoVDO

Stanford Seminar - Efficient and Resilient Systems in the Cognitive Era

Offered By: Stanford University via YouTube

Tags

Computer Science Courses Statistical Modeling Courses High Performance Computing Courses Energy Efficiency Courses System Architecture Courses Swarm Intelligence Courses

Course Description

Overview

Explore the future of computing systems in the cognitive era through this Stanford seminar. Delve into Pradip Bose's insights on IBM's research history and the emerging challenges in system architecture. Learn about swarm intelligence, cooperative sensor fusion, and the EPOCHS reference application. Discover optimized hardware solutions for embedded AI and techniques for achieving high performance and energy efficiency. Examine innovative approaches like GPU under-volting and statistical modeling of memory errors. Gain valuable knowledge on key focus areas in programmability, efficiency, modularity, and scalability as part of the DARPA DSSOC IBM-led EPOCHS project.

Syllabus

Introduction.
Pradip Bose's IBM Genealogy.
IBM Research: A History of Progress.
A New Era of Computing....
System Architectural Vision for the Cognitive Era.
From Swarm Intelligence to Adaptive Swarm Intelligence.
DSSOC SELECTED PARTICIPANTS.
Cooperative Sensor Fusion: A Key Technical Challenge.
Constructing the EPOCHS Reference Application (ERA).
Optimized Hardware for Embedded Al.
Achieving High Performance and Energy Efficiency: Significant Technical Challenge.
Aggressive GPU Under-Volting Below Vmin.
Statistical modeling of errors in memory.
(DARPA DSSOC) IBM-led EPOCHS: Key Focus Areas Programmability, Efficiency, Modularity, Scalability.


Taught by

Stanford Online

Tags

Related Courses

High Performance Computing
Georgia Institute of Technology via Udacity
Введение в параллельное программирование с использованием OpenMP и MPI
Tomsk State University via Coursera
High Performance Computing in the Cloud
Dublin City University via FutureLearn
Production Machine Learning Systems
Google Cloud via Coursera
LAFF-On Programming for High Performance
The University of Texas at Austin via edX