Carlos Kavka

MULTICUBE: Multi-objective Design Space Exploration of Multi-core Architectures

Technology trends enable the integration of many processor cores in a System-on-Chip (SoC). In these complex architectures, several architectural parameters can be tuned to find the best trade-off in terms of multiple metrics such as energy and delay. The main goal of the MULTICUBE project consists of the definition of an automatic Design Space Exploration framework to support the design of next generation many-core architectures.

Exploiting Web Technologies to Connect Business Process Management and Engineering

The Business Process Model and Notation (BPMN) standard can be used for representing low-level simulation and automation workflows for scientific, engineering and manufacturing processes. This paper focuses on removing the main obstacles that limit a more widespread adoption of the standard and the related technology: collaboration and data management. Web technologies can provide the necessary complementary features to the BPMN editing and execution activities: real-time collaboration, accessibility, information and expertise sharing. The proposed prototype mimics a SaaS (Software-as-a-Service) platform offering public community support and a private working area which can be shared in real-time with other users. The prototype includes an execution engine the implementation of which has been tailored to support the data structures required by scientific and engineering applications. The ideas presented in this paper are supported by three use cases: a Multi Disciplinary Optimization case (which is a typical engineering-domain problem involving the design of complex items), a collaborative decision-making scenario (the negotiation process for generating a lecture timetable at a university) and Lego-like decomposition of an optimization algorithm (its constituent elements can be easily re-assembled and shared with our platform).

Enhancing BPMN 2.0 support for service interaction patterns

Choreography modeling languages have emerged in the past years as a mean for capturing and managing collaborative processes. The advancement of such languages let to the definition of the service interaction patterns, a pattern-based framework for the benchmarking of choreography languages against abstracted forms of representative scenarios. Service interaction patterns have been used to analyze the capabilities of different languages. Since its introduction, no benchmark based on this framework has been performed on the Business Process Model and Notation (BPMN) version 2.0. In this paper, we present an assessment of BPMN 2.0 support for service interaction patterns. We evidence the issues that limit the set of supported patterns, and propose enhancements to overcome them.

The MULTICUBE Design Flow

This chapter introduces the design-flow of the MULTICUBE project whose main goal is the definition of an automatic multi-objective Design Space Exploration (DSE) framework to be used to tune the parameters of System-on-Chip architectures by taking into account the target set of metrics (e.g. energy, latency, throughput, etc.). One of the important goals of the automatic multi-objective DSE framework is to find design trade-offs that best meet system constraints and cost criteria which are indeed strongly dependent on the target application.A set of heuristic optimisation algorithms have been defined to reduce the overall optimization time by identifying an approximated Pareto set of parameter configurations with respect to a set of selected figures of merit. Once the approximated Pareto set is built, the designer can quickly apply decision criteria to select the best configuration satisfying the constraints. The DSE flow is based on the interaction of two frameworks to be used at design time: the Design Space Exploration Framework, a set of opensource and proprietary architectural exploration tools, and the Power/Performance Estimation Framework, a set of modeling and simulation tools (open-source and proprietary) operating at several levels of abstraction. The DSE flow also includes the specification of an XML integration interface to connect the exploration and estimation frameworks and a Run-time Resource Manager exploiting, at run-time, the best software configuration alternatives derived at design-time to optimize the usage of system resources.

MFGA: a GA for complex real-world optimisation problems

We present a multi-objective genetic algorithm called magnifying front genetic algorithm (MFGA) designed in order to treat complex real-world optimisation problems. A first source of complexity is the presence of different input variables classes (real, discrete and categorical). MFGA is able to treat appropriately each of them as well as any combination. Moreover, real-world applications often require a long time to evaluate objective values from input variables. We deal with this issue working on elitism (in order to tune properly the balance between explorative and exploitative capabilities of the algorithm) and introducing a parallel steady-state evolution scheme, which is able to use the available computing resources as much intensively as possible. We test the algorithm on two different scenarios: mathematical benchmarks and real-world applications. For the latter one we chose a problem arising in multi-processor system-on-chip (MPSoC) design, a field which is characterised by discrete and more often categorical variables.

Multi-disciplinary Optimization with Standard Co-simulation Interfaces.

Numerical simulations and optimization are at the base of the design process of modern complex engineering systems. Typically, individual components are simulated by using highly specialized software tools applicable to single or narrow domains (mechanical stress, fluid dynamics, thermodynamics, acoustic, etc.) and then combined together in order to build complex systems to be co-simulated and optimized. This distributed engineering development process requires that model components must be developed in such a way, that they could be easily interchanged between different departments of the same company, may be geographically distributed or even between independent companies. This position paper provides a short discussion about the currently available standards and presents work in progress concerning the definition of new standards for the interconnection of complex engineering systems and its optimization as required in modern engineering design. The paper is complemented with a few examples which provides a base for further discussion.

Eco-process Engineering System for Collaborative Product Process System Optimisation

Eco-Process engineering system (EPES) means systematic collaborative eco-efficiency and eco-innovation aspects in product service system (PSS) development and management, and covers all life-cycle phases. It is an ICT tool and related application methodology. The development focus on PSS from functional and cost performance is currently enhanced with sustainability aspects. The goal is to create more value with less environmental impact. In the virtual factories, extended enterprises, the collaboration between different stakeholders, engineers, managers, users of the PSS is a must and all actors in the value chain need a common goal. EPES system provides a collaborative space, covering common data and functionalities for knowledge management, multi-objective decision making, simulation and optimisation. Coordinated evolution (co-evolution) of products, processes and services creates competitive advantage. This paper shows a prototype of EPES system. The software building blocks of EPES system are illustrated as well methodology steps in setting up system and using it.

BPMN 2.0 and the Service Interaction Patterns: Can We Support Them All?

The Business Process Model and Notation (BPMN) specification version 2.0 represents the amalgamation of best practices within the business modeling community to define the notation and semantics of collaboration diagrams, process diagrams and choreography diagrams. Capturing and managing collaborative processes became a hot topic in the past years, and different choreography modeling languages have emerged. The advancement of such languages let to the definition of the service interaction patterns, a framework for the benchmarking of choreography languages against abstracted forms of representative scenarios. In this paper, we present an assessment of BPMN 2.0 support for service interaction patterns. We evidence the issues that limit the set of supported patterns, and propose enhancements to overcome them.

Design Space Exploration of Parallel Architectures

This chapter will present two significant applications of the MULTICUBE design space exploration framework. The first part will present the design space exploration of a low power processor developed by STMicroelectronics by using the modeFRONTIER tool to demonstrate the benefits DSE not only in terms of objective quality, but also in terms of impact on the design process within the corporate environment. The second part will describe the application of RSM models developed within MULTICUBE to a tiled, multiple-instruction, many-core architecture developed by ICT China. Overall, the results have showed that different models can present a trade-off of accuracy versus computational effort. In fact, throughout the evaluation, we observed that high accuracy models require high computational time (for both model construction time and prediction time); vice-versa low model construction and prediction time has led to low accuracy.

Optimization Algorithms for Design Space Exploration of Embedded Systems

This chapter is dedicated to the optimization algorithms developed in the MULTICUBE project and to their surrounding environment. Two software design space exploration (DSE) tools host the algorithms: Multicube Explorer and mode-FRONTIER. The description of the proposed algorithms is the central part of the chapter. The focus will be on newly developed algorithms and on ad-hoc extensions of existing techniques in order to face with discrete and categorical design space parameters that are very common when working with embedded systems design. This chapter will also provide some fundamental guidelines to build a strategy for testing the performance and accuracy of such algorithms. The aim is mainly to build confidence in optimization techniques, rather than to simply compare one algorithm versus another one. The “no-free-lunch theorem for optimization” has to be taken into consideration and therefore the analysis will look forward to robustness and industrial reliability of the results.