Milepost gcc: Machine learning enabled self-tuning compiler

G Fursin, Y Kashnikov, AW Memon, Z Chamski… - International journal of …, 2011 - Springer
Tuning compiler optimizations for rapidly evolving hardware makes porting and extending
an optimizing compiler for each new platform extremely challenging. Iterative optimization is …

Predictive runtime code scheduling for heterogeneous architectures

VJ Jiménez, L Vilanova, I Gelado, M Gil… - … Conference on High …, 2009 - Springer
Heterogeneous architectures are currently widespread. With the advent of easy-to-program
general purpose GPUs, virtually every recent desktop computer is a heterogeneous system …

From warm to hot starts: Leveraging runtimes for the serverless era

J Carreira, S Kohli, R Bruno, P Fonseca - … of the workshop on hot topics …, 2021 - dl.acm.org
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 …

Hhvm jump-start: Boosting both warmup and steady-state performance at scale

G Ottoni, B Liu - 2021 IEEE/ACM International Symposium on …, 2021 - ieeexplore.ieee.org
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 …

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 …

Collective optimization: A practical collaborative approach

G Fursin, O Temam - ACM Transactions on Architecture and Code …, 2010 - dl.acm.org
Iterative optimization is a popular and efficient research approach to optimize programs
using feedback-directed compilation. However, one of the key limitations that prevented …

Exploiting statistical correlations for proactive prediction of program behaviors

Y Jiang, EZ Zhang, K Tian, F Mao, M Gethers… - Proceedings of the 8th …, 2010 - dl.acm.org
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 …

An input-centric paradigm for program dynamic optimizations

K Tian, Y Jiang, EZ Zhang, X Shen - Proceedings of the ACM …, 2010 - dl.acm.org
Accurately predicting program behaviors (eg, locality, dependency, method calling
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 …

Performance metrics and models for shared cache

C Ding, X Xiang, B Bao, H Luo, YW Luo… - Journal of Computer …, 2014 - Springer
Performance metrics and models are prerequisites for scientific understanding and
optimization. This paper introduces a new footprint-based theory and reviews the research …