SPCL_Bcast: Albert Cohen, Can I Cook a 5 o'clock Compiler Cake and Eat It at 2?, Thursday, 7th December, 9AM CET
by Marcin Chrapek
The Scalable Parallel Computing Lab's *SPCL_Bcast* seminar continues
with *Albert Cohen of Google* presenting on *Can I Cook a 5 o'clock
Compiler Cake and Eat It at 2?* Everyone is welcome to attend (over Zoom)!
*When:* Thursday, 7th December, 9AM CET
*Where:* Zoom
Join <https://spcl.inf.ethz.ch/Bcast/join>
*Abstract:* In high-performance computing words: can we build a compiler
that will eventually save a lot of performance engineering effort while
immediately delivering competitive results? Here, competitiveness refers
to achieving near hardware peak-performance for important applications.
The question is particularly hot in a domain-specific setting, where the
building blocks for constructing an effective optimizing compiler may be
inadequate, too generic, or too low-level. It is widely understood that
compiler construction has failed to deliver early afternoon sweets. I
personally feel bad about it, but until recently it remained an academic
exercise to challenge the status quo. Maybe it is now time to reconsider
this assumption: ML-enhanced compilers become the norm rather than the
exception. New compiler frameworks reconcile optimizations for the
common case with application-specific performance. Domain-specific code
generators play an essential role in the implementation of dense and
sparse numerical libraries. But even with the help of domain-specific
compilers, peak performance can only be achieved at the expense of a
dramatic loss of programmability. Are we ever going to find a way out of
this programmability/performance dilemma? What about the velocity and
agility of compiler engineers? Can we make ML-based heuristics scalable
enough to compile billions of lines of code? Can we do so while enabling
massive code reuse across domains, languages and hardware? We will
review these questions, based on recent successes and half-successes in
academia and industry. We will also form an invitation to tackle these
challenges in future research and software development.
*Biography:* Albert Cohen is a research scientist at Google. An alumnus
of École Normale Supérieure de Lyon and the University of Versailles, he
has been a research scientist at Inria, a visiting scholar at the
University of Illinois, an invited professor at Philips Research, and a
visiting scientist at Facebook Artificial Intelligence Research. Albert
works on parallelizing, optimizing and machine learning compilers, and
on dataflow and synchronous programming languages, with applications to
high-performance computing, artificial intelligence and reactive control.
More details & future talks <https://spcl.inf.ethz.ch/Bcast/>
Scalable Parallel Computing Lab (SPCL)
Department of Computer Science, ETH Zurich
Website <https://spcl.inf.ethz.ch> X(Twitter)
<https://twitter.com/spcl_eth> YouTube <https://www.youtube.com/@spcl>
GitHub <https://github.com/spcl>
4 months, 3 weeks