A Configurable Transport Layer for CAF

The message-driven nature of actors lays a foundation for developing scalable and distributed software. While the actor itself has been thoroughly modeled, the message passing layer lacks a common definition. Properties and guarantees of message exchange often shift with implementations and contexts. This adds complexity to the development process, limits portability, and removes transparency from distributed actor systems. In this work, we examine actor communication, focusing on the implementation and runtime costs of reliable and ordered delivery. Both guarantees are often based on TCP for remote messaging, which mixes network transport with the semantics of messaging. However, the choice of transport may follow different constraints and is often governed by deployment. As a first step towards re-architecting actor-to-actor communication, we decouple the messaging guarantees from the transport protocol. We validate our approach by redesigning the network stack of the C++ Actor Framework (CAF) so that it allows to combine an arbitrary transport protocol with additional functions for remote messaging. An evaluation quantifies the cost of composability and the impact of individual layers on the entire stack

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

Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research

Parallel Discrete Event Simulation with Erlang

Discrete Event Simulation (DES) is a widely used technique in which the state of the simulator is updated by events happening at discrete points in time (hence the name). DES is used to model and analyze many kinds of systems, including computer architectures, communication networks, street traffic, and others. Parallel and Distributed Simulation (PADS) aims at improving the efficiency of DES by partitioning the simulation model across multiple processing elements, in order to enabling larger and/or more detailed studies to be carried out. The interest on PADS is increasing since the widespread availability of multicore processors and affordable high performance computing clusters. However, designing parallel simulation models requires considerable expertise, the result being that PADS techniques are not as widespread as they could be. In this paper we describe ErlangTW, a parallel simulation middleware based on the Time Warp synchronization protocol. ErlangTW is entirely written in Erlang, a concurrent, functional programming language specifically targeted at building distributed systems. We argue that writing parallel simulation models in Erlang is considerably easier than using conventional programming languages. Moreover, ErlangTW allows simulation models to be executed either on single-core, multicore and distributed computing architectures. We describe the design and prototype implementation of ErlangTW, and report some preliminary performance results on multicore and distributed architectures using the well known PHOLD benchmark.Comment: Proceedings of ACM SIGPLAN Workshop on Functional High-Performance Computing (FHPC 2012) in conjunction with ICFP 2012. ISBN: 978-1-4503-1577-

Code management automation for Erlang remote actors

Distributed Erlang provides mechanisms for spawning actors remotely through its remote spawn BIF. However, for remote spawn to function properly, the node hosting the spawned actor must share the same codebase as that of the node launching the actor. This assumption turns out to be too strong for various distributed settings. We propose a higher-level framework for the remote spawn of side effect free actors, abstracting from and automating codebase migration and management.peer-reviewe

OpenCL Actors - Adding Data Parallelism to Actor-based Programming with CAF

The actor model of computation has been designed for a seamless support of concurrency and distribution. However, it remains unspecific about data parallel program flows, while available processing power of modern many core hardware such as graphics processing units (GPUs) or coprocessors increases the relevance of data parallelism for general-purpose computation. In this work, we introduce OpenCL-enabled actors to the C++ Actor Framework (CAF). This offers a high level interface for accessing any OpenCL device without leaving the actor paradigm. The new type of actor is integrated into the runtime environment of CAF and gives rise to transparent message passing in distributed systems on heterogeneous hardware. Following the actor logic in CAF, OpenCL kernels can be composed while encapsulated in C++ actors, hence operate in a multi-stage fashion on data resident at the GPU. Developers are thus enabled to build complex data parallel programs from primitives without leaving the actor paradigm, nor sacrificing performance. Our evaluations on commodity GPUs, an Nvidia TESLA, and an Intel PHI reveal the expected linear scaling behavior when offloading larger workloads. For sub-second duties, the efficiency of offloading was found to largely differ between devices. Moreover, our findings indicate a negligible overhead over programming with the native OpenCL API.Comment: 28 page

A semantics comparison workbench for a concurrent, asynchronous, distributed programming language

A number of high-level languages and libraries have been proposed that offer novel and simple to use abstractions for concurrent, asynchronous, and distributed programming. The execution models that realise them, however, often change over time---whether to improve performance, or to extend them to new language features---potentially affecting behavioural and safety properties of existing programs. This is exemplified by SCOOP, a message-passing approach to concurrent object-oriented programming that has seen multiple changes proposed and implemented, with demonstrable consequences for an idiomatic usage of its core abstraction. We propose a semantics comparison workbench for SCOOP with fully and semi-automatic tools for analysing and comparing the state spaces of programs with respect to different execution models or semantics. We demonstrate its use in checking the consistency of properties across semantics by applying it to a set of representative programs, and highlighting a deadlock-related discrepancy between the principal execution models of SCOOP. Furthermore, we demonstrate the extensibility of the workbench by generalising the formalisation of an execution model to support recently proposed extensions for distributed programming. Our workbench is based on a modular and parameterisable graph transformation semantics implemented in the GROOVE tool. We discuss how graph transformations are leveraged to atomically model intricate language abstractions, how the visual yet algebraic nature of the model can be used to ascertain soundness, and highlight how the approach could be applied to similar languages.Comment: Accepted by Formal Aspects of Computin

The HdpH DSLs for scalable reliable computation

The statelessness of functional computations facilitates both parallelism and fault recovery. Faults and non-uniform communication topologies are key challenges for emergent large scale parallel architectures. We report on HdpH and HdpH-RS, a pair of Haskell DSLs designed to address these challenges for irregular task-parallel computations on large distributed-memory architectures. Both DSLs share an API combining explicit task placement with sophisticated work stealing. HdpH focuses on scalability by making placement and stealing topology aware whereas HdpH-RS delivers reliability by means of fault tolerant work stealing. We present operational semantics for both DSLs and investigate conditions for semantic equivalence of HdpH and HdpH-RS programs, that is, conditions under which topology awareness can be transparently traded for fault tolerance. We detail how the DSL implementations realise topology awareness and fault tolerance. We report an initial evaluation of scalability and fault tolerance on a 256-core cluster and on up to 32K cores of an HPC platform