Milepost gcc: Machine learning enabled self-tuning compiler
Tuning compiler optimizations for rapidly evolving hardware makes porting and extending
an optimizing compiler for each new platform extremely challenging. Iterative optimization is …
an optimizing compiler for each new platform extremely challenging. Iterative optimization is …
Predictive runtime code scheduling for heterogeneous architectures
Heterogeneous architectures are currently widespread. With the advent of easy-to-program
general purpose GPUs, virtually every recent desktop computer is a heterogeneous system …
general purpose GPUs, virtually every recent desktop computer is a heterogeneous system …
From warm to hot starts: Leveraging runtimes for the serverless era
The serverless computing model leverages high-level languages, such as JavaScript and
Java, to raise the level of abstraction for cloud programming. However, today's design of …
Java, to raise the level of abstraction for cloud programming. However, today's design of …
Hhvm jump-start: Boosting both warmup and steady-state performance at scale
Just-In-Time (JIT) compilation is often employed in Virtual Machines (VMs) to translate their
virtual-machine languages into real-machine code. This approach not only brings portability …
virtual-machine languages into real-machine code. This approach not only brings portability …
Evaluating iterative optimization across 1000 datasets
Y Chen, Y Huang, L Eeckhout, G Fursin… - Proceedings of the 31st …, 2010 - dl.acm.org
While iterative optimization has become a popular compiler optimization approach, it is
based on a premise which has never been truly evaluated: that it is possible to learn the best …
based on a premise which has never been truly evaluated: that it is possible to learn the best …
Collective optimization: A practical collaborative approach
Iterative optimization is a popular and efficient research approach to optimize programs
using feedback-directed compilation. However, one of the key limitations that prevented …
using feedback-directed compilation. However, one of the key limitations that prevented …
Exploiting statistical correlations for proactive prediction of program behaviors
This paper presents a finding and a technique on program behavior prediction. The finding
is that surprisingly strong statistical correlations exist among the behaviors of different …
is that surprisingly strong statistical correlations exist among the behaviors of different …
An input-centric paradigm for program dynamic optimizations
Accurately predicting program behaviors (eg, locality, dependency, method calling
frequency) is fundamental for program optimizations and runtime adaptations. Despite …
frequency) is fundamental for program optimizations and runtime adaptations. Despite …
Graalvisor: Virtualized polyglot runtime for serverless applications
R Bruno, S Ivanenko, S Wang, J Stevanovic… - arXiv e …, 2022 - ui.adsabs.harvard.edu
Serverless is a new attractive computing model that offers great scalability and elasticity,
taking the infrastructure management burden away from users, and enabling a pay-as-you …
taking the infrastructure management burden away from users, and enabling a pay-as-you …
Performance metrics and models for shared cache
Performance metrics and models are prerequisites for scientific understanding and
optimization. This paper introduces a new footprint-based theory and reviews the research …
optimization. This paper introduces a new footprint-based theory and reviews the research …