FPTalks 2024 on July 11th!

[Zachary Tatlock]

Howdy folks,

Quick reminder that the annual FPTalks workshop will be Thursday, July 11th this year starting around 7:45am Pacific Time!

For details and (free!) registration, please see: https://fpbench.org/talks/fptalks24.html

Somehow we have an even more exciting lineup of the latest and greatest research from across numerical computing, including tools, program analyses, hardware design, and formulation verification. It's going to be a fantastic event :)

Talks will be over Zoom (we will send the link to all registered attendees) and streamed to YouTube.

Snapshot of the full program below. Please help us out by spreading the word!

Best regards,

Z

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8:00–9:00 PDTSession 1

8-bit Transformer Inference and Fine-tuning for Edge Accelerators

Jeffrey Yu, Stanford University

• Paper

Precision Learning for DNN Compression via Adaptive Quantization

Cédric Gernigon, Inria Rennes

• Paper

Accumulator-Aware Quantization with Guaranteed Overflow Avoidance

Ian Colbert, AMD Software Architecture

• ICCV'23 Paper
 
• ICML'24 Paper

FTTN: Feature-Targeted Testing of NVIDIA & AMD Matrix Accelerators

Xinyi Li, Pacific Northwest National Laboratory

• Paper
 
• Artifact

9:30–10:30 PDTSession 2

Type-based approaches to rounding error analysis

Ariel E. Kellison, Cornell University

• Paper
 
• Artifact

End-to-End Verification of a Fast and Accurate Floating-Point Approximation

Guillaume Melquiond, Université Paris Saclay, Inria

Bit Blasting Probabilistic Programs

Guy Van den Broeck, University of California, Los Angeles

• Paper

A Formal Specification of Tensor Cores via Satisfiability Modulo Theories

Benjamin Valpey, University of Rochester

• Paper

10:30–11:00 PDT

Session 3

Verification of Digital Numerics for High Consequence Systems

Sam Pollard, Sandia National Laboratory

• Research Group

Predicting Performance and Accuracy for Precision Tuning

Yutong Wang, University of California, Davis

• Paper
 
• FPLearner

An Overview of the NASA LaRC Tool Suite for Floating-Point Analysis

Mariano Moscato, NASA LaRC / AMA Inc.

• PRECiSA
 
• ReFlow
 
• VSCode-PRECiSA
 
• PVS Floating-Point Library

Customizing Elementary Function Approximations for Hardware Accelerators

Benjamin Carleton, Cornell University

• Calyx