Scaling Reliably: Improving the Scalability of the Erlang Distributed Actor Platform
| Autor: | Natalia Chechina, Stavros Aronis, Kjell Winblad, Konstantinos Sagonas, Phil Trinder, Katerina Roukounaki, Maurizio Di Stefano, Kenneth MacKenzie, Kenneth Lundin, Olivier Boudeville, Sverker Eriksson, Rickard Green, Stephen Adams, Nikolaos Papaspyrou, Viktória Fördős, Huiqing Li, Csaba Hoch, Eva Bihari, Amir Ghaffari, Francesco Cesarini, Yiannis Tsiouris, Aggelos Giantsios, David Klaftenegger, Robert Baker, Simon Thompson |
|---|---|
| Přispěvatelé: | Simon Thompson, Simon |
| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
Computer science media_common.quotation_subject Distributed computing 02 engineering and technology computer.software_genre Distributed hash table 0202 electrical engineering electronic engineering information engineering media_common computer.programming_language 020203 distributed computing Multi-core processor Computer Science - Programming Languages QA76.76 Stochastic process 020207 software engineering Erlang (programming language) Ant colony Computer Science - Distributed Parallel and Cluster Computing Debugging Virtual machine Scalability Operating system Distributed Parallel and Cluster Computing (cs.DC) computer Software Programming Languages (cs.PL) |
| ISSN: | 0164-0925 |
| DOI: | 10.48550/arxiv.1704.07234 |
| Popis: | Distributed actor languages are an effective means of constructing scalable reliable systems, and the Erlang programming language has a well-established and influential model. While the Erlang model conceptually provides reliable scalability, it has some inherent scalability limits and these force developers to depart from the model at scale. This article establishes the scalability limits of Erlang systems and reports the work of the EU RELEASE project to improve the scalability and understandability of the Erlang reliable distributed actor model. We systematically study the scalability limits of Erlang and then address the issues at the virtual machine, language, and tool levels. More specifically: (1) We have evolved the Erlang virtual machine so that it can work effectively in large-scale single-host multicore and NUMA architectures. We have made important changes and architectural improvements to the widely used Erlang/OTP release. (2) We have designed and implemented Scalable Distributed (SD) Erlang libraries to address language-level scalability issues and provided and validated a set of semantics for the new language constructs. (3) To make large Erlang systems easier to deploy, monitor, and debug, we have developed and made open source releases of five complementary tools, some specific to SD Erlang. Throughout the article we use two case studies to investigate the capabilities of our new technologies and tools: a distributed hash table based Orbit calculation and Ant Colony Optimisation (ACO). Chaos Monkey experiments show that two versions of ACO survive random process failure and hence that SD Erlang preserves the Erlang reliability model. While we report measurements on a range of NUMA and cluster architectures, the key scalability experiments are conducted on the Athos cluster with 256 hosts (6,144 cores). Even for programs with no global recovery data to maintain, SD Erlang partitions the network to reduce network traffic and hence improves performance of the Orbit and ACO benchmarks above 80 hosts. ACO measurements show that maintaining global recovery data dramatically limits scalability; however, scalability is recovered by partitioning the recovery data. We exceed the established scalability limits of distributed Erlang, and do not reach the limits of SD Erlang for these benchmarks at this scale (256 hosts, 6,144 cores). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|