[SPCL_Bcast] Can I Cook a 5 o'clock Compiler Cake and Eat It at 2?

Speaker: Albert Cohen
Venue: SPCL_Bcast #45, recorded on 7th December, 2023
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.
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