Evaluating Scalable Distributed Erlang for Scalability and Reliability

Chechina, Natalia; MacKenzie, Kenneth; Thompson, Simon; Trinder, Phil; Boudeville, Olivier; Fördős, Viktória; Hoch, Csaba; Ghaffari, Amir; Hernandez, Mario Moro

doi:10.1109/tpds.2017.2654246

Cited by 14 publications

(13 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar experiments show consistent results for a range of micro-benchmarks, several benchmarks, and the very substantial (approximately 150K lines of Erlang) Sim-Diasca case study [16] on several state of the art NUMA architectures, and the four clusters specified in Appendix A. A coherent presentation of many of these results is available in an article by [22] and in a RELEASE project deliverable 20 . The bulk of the experiments reported here are conducted on the Athos cluster using Erlang/OTP 17.4 and the associated SD Erlang libraries.…”

Section: Systemic Evaluationsupporting

confidence: 63%

“…A further challenge is how to systematically refactor a distributed Erlang application into SD Erlang, and this is outlined in Section i. A detailed discussion of distributed system design and refactoring in SD Erlang provided in a recent article [22].…”

Section: Registered_names({nodenode})mentioning

confidence: 99%

“…Deployment The deployment and monitoring of ACO, and of the large (150K lines of Erlang) Sim-Diasca simulation using WombatOAM (Section ii) on the Athos cluster is detailed in [22].…”

Section: Ant Colony Optimisation (Aco)mentioning

confidence: 99%

“…All of the performance results in Section VIII are entirely new, although a comprehensive study of SD Erlang performance is now available in a recent article by [22].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Scaling Reliably

Trinder

Chechina

Papaspyrou

et al. 2017

ACM Trans. Program. Lang. Syst.

Self Cite

View full text Add to dashboard Cite

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 (6144 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, 6144 cores).

show abstract

Section: Systemic Evaluationsupporting

confidence: 63%

Section: Registered_names({nodenode})mentioning

confidence: 99%

“…Deployment The deployment and monitoring of ACO, and of the large (150K lines of Erlang) Sim-Diasca simulation using WombatOAM (Section ii) on the Athos cluster is detailed in [22].…”

Section: Ant Colony Optimisation (Aco)mentioning

confidence: 99%

“…All of the performance results in Section VIII are entirely new, although a comprehensive study of SD Erlang performance is now available in a recent article by [22].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Scaling Reliably

Trinder

Chechina

Papaspyrou

et al. 2017

ACM Trans. Program. Lang. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…To date SD Erlang has been shown to deliver significant performance benefits above 40 hosts using some relatively simple benchmarks [5]. The Ant Colony Optimisation (ACO) is a parallel simulation benchmark, and the core of the Orbit benchmark is a non-replicated DHT, similar to NoSQL DBMS like Riak [2].…”

Section: Introductionmentioning

confidence: 99%

A scalable reliable instant messenger using the SD Erlang libraries

Chechina

Hernandez

Trinder

2016

Proceedings of the 15th International Workshop on Erlang

Self Cite

View full text Add to dashboard Cite

Erlang has world leading reliability capabilities, but while it scales extremely well within a single node, distributed Erlang has some scalability issues. The Scalable Distributed (SD) Erlang libraries have been designed to address the scalability limitations while preserving the reliability model, and shown to deliver significant performance benefits above 40 hosts using some relatively simple benchmarks.This paper compares the reliability and scalability of SD Erlang and distributed Erlang using an Instant Messaging (IM) server benchmark that is a far more typical Erlang application; a relatively large and sophisticated benchmark; has throughput as the key performance metric; and uses non-trivial reliability mechanisms. We provide a careful reliability evaluation using chaos monkey.The key performance results consider scenarios with and without failures on up to 17 server hosts (272 cores). We show that SD Erlang adds no performance overhead when all nodes are grouped in a single s_group. However, either adding redundant router nodes in distributed Erlang applications, or dividing a set of nodes into small s_groups in SD Erlang applications, have small negative impact. Both the distributed Erlang and SD Erlang IM tolerate failures and, up to the failure rates measured, the failures have no impact on throughput. The IM implementations show that SD Erlang preserves the distributed Erlang reliability properties and mechanisms.

show abstract

Actors@BIM: A Hybrid Formal Model for Cognitive Buildings

Raj,

Kar

2023

Digital Innovations in Architecture, Engineering and Construction

View full text Add to dashboard Cite

Evaluating Scalable Distributed Erlang for Scalability and Reliability

Cited by 14 publications

References 22 publications

Scaling Reliably

Scaling Reliably

A scalable reliable instant messenger using the SD Erlang libraries

Actors@BIM: A Hybrid Formal Model for Cognitive Buildings

Contact Info

Product

Resources

About