User Tools

Site Tools


melange:schedule

Schedule : Spring 2021

This is the tentative schedule of Mélange group for the Spring 2021 semester.
Meeting time & Place : Mondays 12:00 PM - 1:00 PM (MST) via Webex

WEEK DATE TOPIC PRESENTER
1 01/29/2021 Intro meeting
2 02/08/2021 Planning
3 02/15/2021 From High-Level Inference Algorithms to Efficient Code (link) William Scarbro
4 02/22/2021 Software for polyhedral compilation (link1,link2,link3) Louis-Noel Pouchet
5 03/01/2021 Analytical Characterization and Design Space Exploration for Optimization of CNNs (link) Chiranjeb Mondal
6 03/08/2021 Open discussion
7 03/15/2021 Program transformations for energy efficiency Louis Narmour
8 03/22/2021 Graph-based, Self-Supervised Program Repair from Diagnostic Feedback (link) Steve Kommrusch
9 03/29/2021 Canonical Facet Allocation: A Burst-Friendly Data Layout Corentin Ferry
10 04/05/2021 Cancelled
11 04/12/2021 Spring break
12 04/19/2021 Type-directed scheduling of streaming accelerators link) Prerana Ghalsasi
13 04/26/2021 Tensorflow Sanjay Rajopadhye
14 05/03/2021 Intel CnC (link) and the PIPES compiler (link) Alexandre Dubois
15 05/10/2021

Previous Semesters, including legacy reading lists

Standard paper study questions

  1. Write a short (max 5 sentences) summary of the paper.
  2. What is the problem addressed in the paper?
  3. Why is the problem important?
  4. How do the authors address the problem?
  5. How do they evaluate their approach?
  6. What is the punch-line (key cool idea, or “what I got out of this paper”)? This is often different for different people and different from what the authors may have intended.
  7. Make a list of deeper questions that you would like discussed in the meeting.

Current Reading Pool

  • Nathanaël Courant, Xavier Leroy. Verified Code Generation for the Polyhedral Model. In Proc. ACM Program. Lang., POPL, 2021. https://doi.org/10.1145/3434321
  • Rui Li, Yufan Xu, Aravind Sukumaran-Rajam, Atanas Rountev, P. Sadayappan. Analytical Characterization and Design Space Exploration for Optimization of CNNs. In The ACM Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS, 2021. https://arxiv.org/pdf/2101.09808.pdf
  • Rajan Walia, Praveen Narayanan, Jacques Carette, Sam Tobin-Hochstadt, Chung-chieh Shan. From High-Level Inference Algorithms to Efficient Code. In Proc. ACM Program. Lang., ICFP, 2019. https://doi.org/10.1145/3341702
melange/schedule.txt · Last modified: 2021/05/03 19:17 by lnarmour