11,574 research outputs found
Multi-Threaded Actors
In this paper we introduce a new programming model of multi-threaded actors
which feature the parallel processing of their messages. In this model an actor
consists of a group of active objects which share a message queue. We provide a
formal operational semantics, and a description of a Java-based implementation
for the basic programming abstractions describing multi-threaded actors.
Finally, we evaluate our proposal by means of an example application.Comment: In Proceedings ICE 2016, arXiv:1608.0313
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
Actors: The Ideal Abstraction for Programming Kernel-Based Concurrency
GPU and multicore hardware architectures are commonly
used in many different application areas to accelerate problem solutions
relative to single CPU architectures. The typical approach to accessing
these hardware architectures requires embedding logic into the programming
language used to construct the application; the two primary forms
of embedding are: calls to API routines to access the concurrent functionality,
or pragmas providing concurrency hints to a language compiler
such that particular blocks of code are targeted to the concurrent functionality.
The former approach is verbose and semantically bankrupt,
while the success of the latter approach is restricted to simple, static
uses of the functionality.
Actor-based applications are constructed from independent, encapsulated
actors that interact through strongly-typed channels. This paper
presents a first attempt at using actors to program kernels targeted at
such concurrent hardware. Besides the glove-like fit of a kernel to the actor
abstraction, quantitative code analysis shows that actor-based kernels
are always significantly simpler than API-based coding, and generally
simpler than pragma-based coding. Additionally, performance measurements
show that the overheads of actor-based kernels are commensurate
to API-based kernels, and range from equivalent to vastly improved for
pragma-based annotations, both for sample and real-world applications
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
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
Graph-RAT programming environment
Graph-RAT is a new programming environment specializing in relational data mining. It incorporates a number of different techniques into a single framework for data collection, data cleaning, propositionalization, and analysis. The language is functional where algorithms are executed over arbitrary sub-graphs of the data. Analytical results can be conducted using collaborative filtering or machine learning techniques. The example algorithms are under BSD license
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