907 research outputs found
Towards Composable Concurrency Abstractions
In the past decades, many different programming models for managing concurrency in applications have been proposed, such as the actor model, Communicating Sequential Processes, and Software Transactional Memory. The ubiquity of multi-core processors has made harnessing concurrency even more important. We observe that modern languages, such as Scala, Clojure, or F#, provide not one, but \emphmultiple concurrency models that help developers manage concurrency. Large end-user applications are rarely built using just a single concurrency model. Programmers need to manage a responsive UI, deal with file or network I/O, asynchronous workflows, and shared resources. Different concurrency models facilitate different requirements. This raises the issue of how these concurrency models interact, and whether they are \emphcomposable. After all, combining different concurrency models may lead to subtle bugs or inconsistencies. In this paper, we perform an in-depth study of the concurrency abstractions provided by the Clojure language. We study all pairwise combinations of the abstractions, noting which ones compose without issues, and which do not. We make an attempt to abstract from the specifics of Clojure, identifying the general properties of concurrency models that facilitate or hinder composition
CPL: A Core Language for Cloud Computing -- Technical Report
Running distributed applications in the cloud involves deployment. That is,
distribution and configuration of application services and middleware
infrastructure. The considerable complexity of these tasks resulted in the
emergence of declarative JSON-based domain-specific deployment languages to
develop deployment programs. However, existing deployment programs unsafely
compose artifacts written in different languages, leading to bugs that are hard
to detect before run time. Furthermore, deployment languages do not provide
extension points for custom implementations of existing cloud services such as
application-specific load balancing policies.
To address these shortcomings, we propose CPL (Cloud Platform Language), a
statically-typed core language for programming both distributed applications as
well as their deployment on a cloud platform. In CPL, application services and
deployment programs interact through statically typed, extensible interfaces,
and an application can trigger further deployment at run time. We provide a
formal semantics of CPL and demonstrate that it enables type-safe, composable
and extensible libraries of service combinators, such as load balancing and
fault tolerance.Comment: Technical report accompanying the MODULARITY '16 submissio
Reasoning about Programs With Effects
AbstractThis note presents a summary of my research on reasoning about programs with effects. This work has been carried out in collaboration with several colleagues over roughly the past ten years. The work has had two major sub-themes: reasoning about functional programs extended with imperative features; and reasoning about components of open distributed systems. Functional programming languages extended with imperative features include languages like Scheme and ML as well as object-based languages such as Java. This work has focused on operationally based semantics and formalisms for specifying and reasoning about such programs. The work on components of open distributed systems has been based on the actor model of computation and has focused on developing semantic models for modular specification and composition of actor systems
Pando: Personal Volunteer Computing in Browsers
The large penetration and continued growth in ownership of personal
electronic devices represents a freely available and largely untapped source of
computing power. To leverage those, we present Pando, a new volunteer computing
tool based on a declarative concurrent programming model and implemented using
JavaScript, WebRTC, and WebSockets. This tool enables a dynamically varying
number of failure-prone personal devices contributed by volunteers to
parallelize the application of a function on a stream of values, by using the
devices' browsers. We show that Pando can provide throughput improvements
compared to a single personal device, on a variety of compute-bound
applications including animation rendering and image processing. We also show
the flexibility of our approach by deploying Pando on personal devices
connected over a local network, on Grid5000, a French-wide computing grid in a
virtual private network, and seven PlanetLab nodes distributed in a wide area
network over Europe.Comment: 14 pages, 12 figures, 2 table
A Concurrency-Agnostic Protocol for Multi-Paradigm Concurrent Debugging Tools
Today's complex software systems combine high-level concurrency models. Each
model is used to solve a specific set of problems. Unfortunately, debuggers
support only the low-level notions of threads and shared memory, forcing
developers to reason about these notions instead of the high-level concurrency
models they chose.
This paper proposes a concurrency-agnostic debugger protocol that decouples
the debugger from the concurrency models employed by the target application. As
a result, the underlying language runtime can define custom breakpoints,
stepping operations, and execution events for each concurrency model it
supports, and a debugger can expose them without having to be specifically
adapted.
We evaluated the generality of the protocol by applying it to SOMns, a
Newspeak implementation, which supports a diversity of concurrency models
including communicating sequential processes, communicating event loops,
threads and locks, fork/join parallelism, and software transactional memory. We
implemented 21 breakpoints and 20 stepping operations for these concurrency
models. For none of these, the debugger needed to be changed. Furthermore, we
visualize all concurrent interactions independently of a specific concurrency
model. To show that tooling for a specific concurrency model is possible, we
visualize actor turns and message sends separately.Comment: International Symposium on Dynamic Language
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Preparing sparse solvers for exascale computing.
Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly parallel sparse solvers are essential for continuing advances in high-fidelity, multi-physics and multi-scale simulations, especially as we target exascale platforms. This paper describes the challenges, strategies and progress of the US Department of Energy Exascale Computing project towards providing sparse solvers for exascale computing platforms. We address the demands of systems with thousands of high-performance node devices where exposing concurrency, hiding latency and creating alternative algorithms become essential. The efforts described here are works in progress, highlighting current success and upcoming challenges. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'
Early aspects: aspect-oriented requirements engineering and architecture design
This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications
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