Sorin Manolache

Fault and energy-aware communication mapping with guaranteed latency for applications implemented on NoC

As feature sizes shrink, transient failures of on-chip network links become a critical problem. At the same time, many applications require guarantees on both message arrival probability and response time. We address the problem of transient link failures by means of temporally and spatially redundant transmission of messages, such that designer-imposed message arrival probabilities are guaranteed. Response time minimisation is achieved by a heuristic that statically assigns multiple copies of each message to network links, intelligently combining temporal and spatial redundancy. Concerns regarding energy consumption are addressed in two ways. Firstly, we reduce the total amount of transmitted messages, and, secondly, we minimise the application response time such that the resulted time slack can be exploited for energy savings through voltage reduction. The advantages of the proposed approach are guaranteed message arrival probability and guaranteed worst case application response time.

Schedulability analysis of applications with stochastic task execution times

In the past decade, the limitations of models considering fixed (worst-case) task execution times have been acknowledged for large application classes within soft real-time systems. A more realistic model considers the tasks having varying execution times with given probability distributions. Considering such a model with specified task execution time probability distribution functions, an important performance indicator of the system is the expected deadline miss ratio of the tasks and of the task graphs. This article presents an approach for obtaining this indicator in an analytic way. Our goal is to keep the analysis cost low, in terms of required analysis time and memory, while considering as general classes of target application models as possible. The following main assumptions have been made on the applications that are modeled as sets of task graphs: the tasks are periodic, the task execution times have given generalized probability distribution functions, the task execution deadlines are given and arbitrary, the scheduling policy can belong to practically any class of non-preemptive scheduling policies, and a designer supplied maximum number of concurrent instantiations of the same task graph is tolerated in the system. Experiments show the efficiency of the proposed technique for monoprocessor systems.

Memory and time-efficient schedulability analysis of task sets with stochastic execution time

This paper presents an efficient way to analyse the performance of task sets, where the task execution time is specified as a generalized continuous probability distribution. We consider fixed task sets of periodic, possibly dependent, non-pre-emptable tasks with deadlines less than or equal to the period. Our method is not restricted to any specific scheduling policy and supports policies with both dynamic and static priorities. An algorithm to construct the underlying stochastic process in a memory and time efficient way is presented. We discuss the impact of various parameters on complexity, in terms of analysis time and required memory. Experimental results show the efficiency of the proposed approach.

Task mapping and priority assignment for soft real-time applications under deadline miss ratio constraints

Both analysis and design optimisation of real-time systems has predominantly concentrated on considering hard real-time constraints. For a large class of applications, however, this is both unrealistic and leads to unnecessarily expensive implementations. This paper addresses the problem of task priority assignment and task mapping in the context of multiprocessor applications with stochastic execution times and in the presence of constraints on the percentage of missed deadlines. We propose a design space exploration strategy together with a fast method for system performance analysis. Experiments emphasize the efficiency of the proposed analysis method and optimisation heuristic in generating high-quality implementations of soft real-time systems with stochastic task execution times and constraints on deadline miss ratios.

Buffer Space Optimisation with Communication Synthesis and Traffic Shaping for NoCs

This paper addresses communication optimisation for applications implemented on networks-on-chip. The mapping of data packets to network links and the timing of the release of the packets are critical for avoiding destination contention. This reduces the demand for communication buffers with obvious advantages in chip area and energy savings. We propose a buffer need analysis approach and a strategy for communication synthesis and packet release timing with minimum communication buffer demand that guarantees worst-case response times

Modelling of real-time embedded systems in an object-oriented design environment with UML

The paper explores aspects concerning system-level specification, modelling and simulation of real time embedded system. By means of case studies, we investigate how object oriented methodologies, and in particular UML, support the modelling of industrial scale real time systems, and how different architectures can be explored by model simulation. We are mainly interested in the problem of system specification as it appears from the prospect of the whole design process. The discussion is illustrated by a large system model from the telecommunications area, the GSM base transceiver station.

Schedulability analysis of multiprocessor real-time applications with stochastic task execution times

This paper presents an approach to the analysis of task sets implemented on multiprocessor systems, when the task execution times are specified as generalized probability distributions. Because of the extreme complexity of the problem, an exact solution is practically impossible to be obtained even for toy examples. Therefore, our methodology is based on approximating the generalized probability distributions of execution times by Coxian distributions of exponentials. Thus, we transform the generalized semi-Markov process, corresponding to the initial problem, into a continuous Markov chain (CTMC) which, however, is extremely large and, hence, most often is impossible to be stored in memory. We have elaborated a solution which allows to generate and analyze the CTMC in an efficient way, such that only a small part has to be stored at a given time. Several experiments investigate the impact of various parameters on complexity, in terms of time and memory, as well as the trade-offs regarding the accuracy of generated results.

Optimization of soft real-time systems with deadline miss ratio constraints

Both analysis and design optimization of real-time systems has predominantly concentrated on considering hard real-time constraints. For a large class of applications, however, this is both unrealistic and leads to unnecessarily expensive implementations. We address the problem of task priority assignment and task mapping in the context of multiprocessor applications with stochastic execution times and in the presence of constraints on the percentage of missed deadlines. We propose a design space exploration strategy based on tabu search together with a fast method for system performance analysis. Experiments emphasize the efficiency of the proposed analysis method and optimization heuristic in generating high quality implementations of soft real-time systems with stochastic task execution times and constraints on deadline miss ratios.

Fault-aware communication mapping for NoCs with guaranteed latency

As feature sizes shrink, transient failures of on-chip network links become a critical problem. At the same time, many applications require guarantees on both message arrival probability and response time. We address the problem of transient link failures by means of temporally and spatially redundant transmission of messages, such that designer-imposed message arrival probabilities are guaranteed. Response time minimisation is achieved by a heuristic that statically assigns multiple copies of each message to network links, intelligently combining temporal and spatial redundancy. Concerns regarding energy consumption are addressed in two ways. First, we reduce the total amount of transmitted messages, and, second, we minimise the application response time such that the resulted time slack can be exploited for energy savings through voltage reduction. The advantages of the proposed approach are guaranteed message arrival probability and guaranteed worst case application response time.