Sun 18 Jun 2023 09:40 - 10:00 at Magnolia 18 - EGRAPHS: Optimization

Numerical hardware design requires aggressive optimization, where designers exploit branch constraints, creating optimization opportunities that are valid only on a sub-domain of input space. We developed an RTL optimization tool that automatically learns the consequences of conditional branches and exploits that knowledge to enable deep optimization. The tool deploys custom built program analysis based on abstract interpretation theory, which when combined with a data-structure known as an e-graph simplifies complex reasoning about program properties. Our tool fully-automatically discovers known floating-point architectures from the computer arithmetic literature and out-performs baseline EDA tools, generating up to 33% faster and 41% smaller circuits.

Sun 18 Jun

Displayed time zone: Eastern Time (US & Canada) change

09:00 - 11:00
09:40
20m
Talk
Automating Constraint-Aware Datapath Optimization using E-Graphs
EGRAPHS
Samuel Coward Imperial College London, UK / Intel Corporation, George A. Constantinides Imperial College London, UK, Theo Drane Intel Corporation, USA
Pre-print File Attached
10:00
20m
Talk
egglog In Practice: Automatically Improving Floating-point Error
EGRAPHS
Oliver Flatt University of Washington, Yihong Zhang University of Washington
10:20
20m
Talk
Optimizing Stateful Dataflow with Local Rewrites
EGRAPHS
Shadaj Laddad University of California at Berkeley, Conor Power University of California at Berkeley, Tyler Hou University of California, Berkeley, Alvin Cheung University of California at Berkeley, Joseph M. Hellerstein University of California, Berkeley
Pre-print File Attached
10:40
20m
Talk
Egg-smol Python: A Pythonic Library for E-graphs
EGRAPHS
Link to publication Pre-print