Optimal infinite scheduling for multi-priced timed automata

This paper is concerned with the derivation of infinite schedules for timed automata that are in some sense optimal. To cover a wide class of optimality criteria we start out by introducing an extension of the (priced) timed automata model that includes both costs and rewards as separate modelling features. A precise definition is then given of what constitutes optimal infinite behaviours for this class of models. We subsequently show that the derivation of optimal non-terminating schedules for such double-priced timed automata is computable. This is done by a reduction of the problem to the determination of optimal mean-cycles in finite graphs with weighted edges. This reduction is obtained by introducing the so-called corner-point abstraction, a powerful abstraction technique of which we show that it preserves optimal schedules

Elasticity and Petri nets

Digital electronic systems typically use synchronous clocks and primarily assume fixed duration of their operations to simplify the design process. Time elastic systems can be constructed either by replacing the clock with communication handshakes (asynchronous version) or by augmenting the clock with a synchronous version of a handshake (synchronous version). Time elastic systems can tolerate static and dynamic changes in delays (asynchronous case) or latencies (synchronous case) of operations that can be used for modularity, ease of reuse and better power-delay trade-off. This paper describes methods for the modeling, performance analysis and optimization of elastic systems using Marked Graphs and their extensions capable of describing behavior with early evaluation. The paper uses synchronous elastic systems (aka latency-tolerant systems) for illustrating the use of Petri nets, however, most of the methods can be applied without changes (except changing the delay model associated with events of the system) to asynchronous elastic systems.Peer ReviewedPostprint (author's final draft

Architectural Adaptation for Application-Specific Locality Optimizations

We propose a machine architecture that integrates programmable logic into key components of the system with the goal of customizing architectural mechanisms and policies to match an application. This approach presents an improvement over traditional approach of exploiting programmable logic as a separate co-processor by preserving machine usability through software and over traditional computer architecture by providing applicationspecific hardware assists. We present two case studies of architectural customization to enhance latency tolerance and efficiently utilize network bisection on multiprocessors for sparse matrix computations. We demonstrate that application-specific hardware assists and policies can provide substantial improvements in performance on a per application basis. Based on these preliminary results, we propose that an application-driven machine customization provides a promising approach to achieve high performance and combat performance fragility. 1 Introduction Tec..

Architectural adaptation for application-specific locality optimizations

We propose a machine architecture that integrates programmable logic into key components of the system with the goal of customizing architectural mechanisms and policies to match an application. This approach presents an improvement over traditional approach of exploiting programmable logic as a separate co-processor by preserving machine usability through software and over traditional computer architecture by providing application-specific hardware assists. We present two case studies of architectural customization to enhance latency tolerance and efficiently utilize network bisection on multiprocessors for sparse matrix computations. We demonstrate that using application-specific hardware assists and policies can provide substantial improvements in performance on a per application basis. Based on these preliminary results, we propose that an application-driven machine customization provides a promising approach to achieve high performance and combat performance fragility

Discovering interesting cycles in directed graphs

Cycles in graphs often signify interesting processes. For example, cyclic trading patterns can indicate inefficiencies or economic dependencies in trade networks, cycles in food webs can identify fragile dependencies in ecosystems, and cycles in financial transaction networks can be an indication of money laundering. Identifying such interesting cycles, which can also be constrained to contain a given set of query nodes, although not extensively studied, is thus a problem of considerable importance. In this paper, we introduce the problem of discovering interesting cycles in graphs. We first address the problem of quantifying the extent to which a given cycle is interesting for a particular analyst. We then show that finding cycles according to this interestingness measure is related to the longest cycle and maximum mean-weight cycle problems (in the unconstrained setting) and to the maximum Steiner cycle and maximum mean Steiner cycle problems (in the constrained setting). A complexity analysis shows that finding interesting cycles is NP-hard, and is NP-hard to approximate within a constant factor in the unconstrained setting, and within a factor polynomial in the input size for the constrained setting. The latter inapproximability result implies a similar result for the maximum Steiner cycle and maximum mean Steiner cycle problems. Motivated by these hardness results, we propose a number of efficient heuristic algorithms. We verify the effectiveness of the proposed methods and demonstrate their practical utility on two real-world use cases: a food web and an international trade-network dataset