Extending and Implementing the Self-adaptive Virtual Processor for Distributed Memory Architectures

Many-core architectures of the future are likely to have distributed memory organizations and need fine grained concurrency management to be used effectively. The Self-adaptive Virtual Processor (SVP) is an abstract concurrent programming model which can provide this, but the model and its current implementations assume a single address space shared memory. We investigate and extend SVP to handle distributed environments, and discuss a prototype SVP implementation which transparently supports execution on heterogeneous distributed memory clusters over TCP/IP connections, while retaining the original SVP programming model

The TASTE Toolset: turning human designed heterogeneous systems into computer built homogeneous software.

The TASTE tool-set results from spin-off studies of the ASSERT project, which started in 2004 with the objective to propose innovative and pragmatic solutions to develop real-time software. One of the primary targets was satellite flight software, but it appeared quickly that their characteristics were shared among various embedded systems. The solutions that we developed now comprise a process and several tools ; the development process is based on the idea that real-time, embedded systems are heterogeneous by nature and that a unique UML-like language was not helping neither their construction, nor their validation. Rather than inventing yet another "ultimate" language, TASTE makes the link between existing and mature technologies such as Simulink, SDL, ASN.1, C, Ada, and generates complete, homogeneous software-based systems that one can straightforwardly download and execute on a physical target. Our current prototype is moving toward a marketed product, and sequel studies are already in place to support, among others, FPGA systems

CSP design model and tool support

The CSP paradigm is known as a powerful concept for designing and analysing the architectural and behavioural parts of concurrent software. Although the theory of CSP is useful for mathematicians, the programming language occam has been derived from CSP that is useful for any engineering practice. Nowadays, the concept of occam/CSP can be used for almost every object-oriented programming language. This paper describes a tree-based description model and prototype tool that elevates the use of occam/CSP concepts at the design level and performs code generation to Java, C, C++, and machine-readable CSP for the level of implementation. The tree-based description model can be used to browse through the generated source code. The tool is a kind of browser that is able to assist modern workbenches (like Borland Builder, Microsoft Visual C++ and 20-SIM) with coding concurrency. The tool will guide the user through the design trajectory using support messages and several semantic and syntax rule checks. The machine-readable CSP can be read by FDR, enabling more advanced analysis on the design. Early experiments with the prototype tool show that the browser concept, combined with the tree-based description model, enables a user-friendly way to create a design using the CSP concepts and benefits. The design tool is available from our URL, http://www.rt.el.utwente.nl/javapp

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

Event notification services: analysis and transformation of profile definition languages

The integration of event information from diverse event notification sources is, as with meta-searching over heterogeneous search engines, a challenging task. Due to the complexity of profile definition languages, known solutions for heterogeneous searching cannot be applied for event notification. In this technical report, we propose transformation rules for profile rewriting. We transform each profile defined at a meta-service into a profile expressed in the language of each event notification source. Due to unavoidable asymmetry in the semantics of different languages, some superfluous information may be delivered to the meta-service. These notifications are then post-processed to reduce the number of spurious messages. We present a survey and classification of profile definition languages for event notification, which serves as basis for the transformation rules. The proposed rules are implemented in a prototype transformation module for a Meta-Service for event notification

The role of concurrency in an evolutionary view of programming abstractions

In this paper we examine how concurrency has been embodied in mainstream programming languages. In particular, we rely on the evolutionary talking borrowed from biology to discuss major historical landmarks and crucial concepts that shaped the development of programming languages. We examine the general development process, occasionally deepening into some language, trying to uncover evolutionary lineages related to specific programming traits. We mainly focus on concurrency, discussing the different abstraction levels involved in present-day concurrent programming and emphasizing the fact that they correspond to different levels of explanation. We then comment on the role of theoretical research on the quest for suitable programming abstractions, recalling the importance of changing the working framework and the way of looking every so often. This paper is not meant to be a survey of modern mainstream programming languages: it would be very incomplete in that sense. It aims instead at pointing out a number of remarks and connect them under an evolutionary perspective, in order to grasp a unifying, but not simplistic, view of the programming languages development process

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'

Towards Exascale Scientific Metadata Management

Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination between the data production and the analysis phases hinges on the availability of metadata that describe the scientific datasets. Existing workflow engines have been capturing a limited form of metadata to provide provenance information about the identity and lineage of the data. However, much of the data produced by simulations, experiments, and analyses still need to be annotated manually in an ad hoc manner by domain scientists. Systematic and transparent acquisition of rich metadata becomes a crucial prerequisite to sustain and accelerate the pace of scientific innovation. Yet, ubiquitous and domain-agnostic metadata management infrastructure that can meet the demands of extreme-scale science is notable by its absence. To address this gap in scientific data management research and practice, we present our vision for an integrated approach that (1) automatically captures and manipulates information-rich metadata while the data is being produced or analyzed and (2) stores metadata within each dataset to permeate metadata-oblivious processes and to query metadata through established and standardized data access interfaces. We motivate the need for the proposed integrated approach using applications from plasma physics, climate modeling and neuroscience, and then discuss research challenges and possible solutions