Evaluating Scalable Distributed Erlang for Scalability and Reliability

Large scale servers with hundreds of hosts and tens of thousands of cores are becoming common. To exploit these platforms software must be both scalable and reliable, and distributed actor languages like Erlang are a proven technology in this area. While distributed Erlang conceptually supports the engineering of large scale reliable systems, in practice it has some scalability limits that force developers to depart from the standard language mechanisms at scale. In earlier work we have explored these scalability limitations, and addressed them by providing a Scalable Distributed (SD) Erlang library that partitions the network of Erlang Virtual Machines (VMs) into scalable groups (s_groups). This paper presents the first systematic evaluation of SD Erlang s_groups and associated tools, and how they can be used. We present a comprehensive evaluation of the scalability and reliability of SD Erlang using three typical benchmarks and a case study. We demonstrate that s_groups improve the scalability of reliable and unreliable Erlang applications on up to 256 hosts (6,144 cores). We show that SD Erlang preserves the class-leading distributed Erlang reliability model, but scales far better than the standard model. We present a novel, systematic, and tool-supported approach for refactoring distributed Erlang applications into SD Erlang. We outline the new and improved monitoring, debugging and deployment tools for large scale SD Erlang applications. We demonstrate the scaling characteristics of key tools on systems comprising up to 10 K Erlang VMs

Revisiting Actor Programming in C++

The actor model of computation has gained significant popularity over the last decade. Its high level of abstraction makes it appealing for concurrent applications in parallel and distributed systems. However, designing a real-world actor framework that subsumes full scalability, strong reliability, and high resource efficiency requires many conceptual and algorithmic additives to the original model. In this paper, we report on designing and building CAF, the "C++ Actor Framework". CAF targets at providing a concurrent and distributed native environment for scaling up to very large, high-performance applications, and equally well down to small constrained systems. We present the key specifications and design concepts---in particular a message-transparent architecture, type-safe message interfaces, and pattern matching facilities---that make native actors a viable approach for many robust, elastic, and highly distributed developments. We demonstrate the feasibility of CAF in three scenarios: first for elastic, upscaling environments, second for including heterogeneous hardware like GPGPUs, and third for distributed runtime systems. Extensive performance evaluations indicate ideal runtime behaviour for up to 64 cores at very low memory footprint, or in the presence of GPUs. In these tests, CAF continuously outperforms the competing actor environments Erlang, Charm++, SalsaLite, Scala, ActorFoundry, and even the OpenMPI.Comment: 33 page

Scaling Reliably: Improving the Scalability of the Erlang Distributed Actor Platform

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 scal

Performance Portability Through Semi-explicit Placement in Distributed Erlang

We consider the problem of adapting distributed Erlang applications to large or heterogeneous architectures to achieve good performance in a portable way. In many architectures, and especially large architectures, the communication latency between pairs of virtual machines (nodes) is no longer uniform. We propose two language-level methods that enable programs to automatically adapt to heterogeneity and non-uniform communication latencies, and both provide information enabling a program to identify an appropriate node when spawning a process. We provide a means of recording node attributes describing the hardware and software capabilities of nodes, and mechanisms that allow an application to examine the attributes of remote nodes. We provide an abstraction of communication distances that enables an application to select nodes to facilitate efficient communication. We have developed open source libraries that implement these ideas. We show that the use of attributes for node selection can lead to significant performance improvements if different components of the application have different processing requirements. We report a detailed empirical investigation of non-uniform communication times in several representative architectures, and show that our abstract model provides a good description of the hierarchy of communication times

The Missing Link! A New Skeleton for Evolutionary Multi-agent Systems in Erlang

Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applications that are in use today. In this paper, we present a new generic skeleton in Erlang for parallel EMAS computations. The skeleton enables us to capture a wide variety of concrete evolutionary computations that can exploit the same underlying parallel implementation. We demonstrate the use of our skeleton on two different evolutionary computing applications: (1) computing the minimum of the Rastrigin function; and (2) solving an urban traffic optimisation problem. We show that we can obtain very good speedups (up to 142.44 ×× the sequential performance) on a variety of different parallel hardware, while requiring very little parallelisation effort.Publisher PDFPeer reviewe

DESIGNING A FRAMEWORK FOR RESTFUL MULTI-AGENT SYSTEMS

Nowadays there are many systems that require some degree of automation. To attain this automation, agent technology has generally been found to be a promising approach. An agent is a piece of software that does activities on behalf of a user or another program. However, designing and deploying an agent infrastructure that achieves scalability is still a major challenge. In this thesis, a pattern for designing agents following RESTful principles is proposed in an effort to address the aforementioned challenges. In addition, the pattern will follow the FIPA Abstract Architecture; which is aimed at developing intelligent agents and supporting interoperability among agents and agent-based systems. Furthermore, an evaluation is done to investigate the scalability of the deployment of a RESTful multi-agent system