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

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

LiquidML: A Web Modeling Language Supporting Fast Metamodel Evolution

Model Driven development approaches are being adopted by the software industry due to a core set of benefits such as raising the level of abstraction and reducing coding errors. However, their underlying modelling languages tend to be quite rigid, making their evolution hard, specifically when the corresponding metamodel do not support primitives and/or functionalities required in specific business domains. In this work, we present an approach for fast evolution of the modelling language that is “self reflective”, allowing modellers to abstract new language concepts from the primitives. The main advantage of our approach is that it provides zero application downtime and automatic tool evolution. As a consequence, applications created with our approach are able to adapt quicker to the business needs than those based on traditional Web modelling languages. We compare our approach with existing modelling languages in a case study providing a proof of its ability to adapt faster than to new business needs.Ministerio de Ciencia e Innovación TIN2013-46928-C3-3-

Towards fast metamodel evolution in LiquidML

The software industry is applying Model-driven development approaches due to a core set of benefits, such as raising the level of abstraction and reducing coding errors. However, their underlying modeling languages tend to be quite static, making their evolution hard, specifically when the corresponding metamodel does not support primitives and/or functionalities required in specific business domains. This paper presents an extension to the LiquidML language to support fast metamodel evolution by allowing experts to abstract new language concepts from primitives while supporting automatic tool evolution and zero application downtime. To probe our claims, we evaluate the evolutionary capabilities of existing modeling languages and LiquidML in a real world language extension.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-R (POLOLAS)Ministerio de Economía y Competitividad TIN2015-71938-RED

Secure Virtualization and Multicore Platforms State-of-the-Art report

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