Generation of dense linear algebra software for shared memory and multicore architectures

Subscribers:
345,000
Published on ● Video Link: https://www.youtube.com/watch?v=i66F0oJwhBU



Duration: 57:32
132 views
2


When writing scientific computing software, programmers often need to identify which algorithm would perform best in a given situation. In dense linear algebra, the answer depends on a large number of factors, ranging from processor type and architectural features to matrix size and performance signature of the used BLAS. In this talk I will show that when targeting shared memory and multicore processors, one must take into account not only different algorithms, but also different types of parallelism. I will illustrate two approaches. One uses blocking and careful scheduling to attain high performance while the other leverages multithreaded BLAS. In addition, I will discuss how the generation of algorithms and code can be automated in both scenarios.




Other Videos By Microsoft Research


2016-09-06Why task-structure matters: The effects of task and social forces on software development
2016-09-06Robust Face Recognition via Sparse Representation
2016-09-06How to make Discretionary Access Control Resistant to Trojan Horses
2016-09-06Modeling Intention in Email: Speech Acts, Information Leaks and User Ranking Methods [1/2]
2016-09-06Techniques and Tools for Engineering Secure Web Applications
2016-09-06Should Machines Emulate Human Speech Recognition?
2016-09-06PLOW: A Collaborative Task Learning Agent
2016-09-06Building Bodies of Knowledge about Software Development Practices
2016-09-06The Manticore Project
2016-09-06Abstractions for event-driven design [1/14]
2016-09-06Generation of dense linear algebra software for shared memory and multicore architectures
2016-09-06The Computation of Economic equilibria [1/2]
2016-09-06Class Morphing: Safely Shaping a Class in the Image of Others [1/3]
2016-09-06Deep Photo and Gigapixel Images
2016-09-06Automated Revision of Distributed and Real-Time Programs
2016-09-06Candidate talk: Knowledge Analysis towards Automatic Question Answering for Discussion Forums
2016-09-06Improving Data Recovery From Embedded Networked Sensing Systems with Fault Detection and Diagnosis
2016-09-06A Discriminative Kernel-based Model to Rank Images from Text Queries
2016-09-06Concurrency Simple and Safe? State of SCOOP
2016-09-06Automated Termination Analysis of Programs using Term Rewriting
2016-09-06Abstraction Methods for Liveness



Tags:
microsoft research