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Monday, March 27 • 08:30 - 09:30
LLVM for the future of Supercomputing

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LLVM is solidifying its foothold in high-performance computing, and as we look forward toward the exascale computing era, LLVM promises to be a cornerstone of our programming environments. In this talk, I'll discuss several of the ways in which we're working to improve LLVM in support of this vision. Ongoing work includes better handling of restrict-qualified pointers [2], optimization of OpenMP constructs [3], and extending LLVM's IR to support an explicit representation of parallelism [4]. We're exploring several ways in which LLVM can be better integrated with autotuning technologies, how we can improve optimization reporting and profiling, and a myriad of other ways we can help move LLVM forward. Much of this effort is now a part of the US Department of Energy's Exascale Computing Project [1]. This talk will start by presenting the big picture, in part discussing goals of performance portability and how those maps into technical requirements, and then discuss details of current and planned development.

[1] https://exascaleproject.org/2016/11/10/ecp-awards-34m-for-software-development/
[2] https://reviews.llvm.org/D9375 (and dependent patches)
[3] https://reviews.llvm.org/D28870 (a first step in this direction)
[4] http://lists.llvm.org/pipermail/llvm-dev/2017-January/108906.html


Hal Finkel

Argonne National Laboratory

Monday March 27, 2017 08:30 - 09:30
E2 2 (Günter Hotz Hall)

Attendees (46)