Exploiting parallelism within multidimensional multirate digital signal processing systems

The intense requirements for high processing rates of multidimensional Digital Signal Processing systems in practical applications justify the Application Specific Integrated Circuits designs and parallel processing implementations. In this dissertation, we propose novel theories, methodologies and architectures in designing high-performance VLSI implementations for general multidimensional multirate Digital Signal Processing systems by exploiting the parallelism within those applications. To systematically exploit the parallelism within the multidimensional multirate DSP algorithms, we develop novel transformations including (1) nonlinear I/O data space transforms, (2) intercalation transforms, and (3) multidimensional multirate unfolding transforms. These transformations are applied to the algorithms leading to systematic methodologies in high-performance architectural designs. With the novel design methodologies, we develop several architectures with parallel and distributed processing features for implementing multidimensional multirate applications. Experimental results have shown that those architectures are much more efficient in terms of execution time and/or hardware cost compared with existing hardware implementations

Exploiting parallelism within multidimensional multirate digital signal processing systems

The intense requirements for high processing rates of multidimensional Digital Signal Processing systems in practical applications justify the Application Specific Integrated Circuits designs and parallel processing implementations. In this dissertation, we propose novel theories, methodologies and architectures in designing high-performance VLSI implementations for general multidimensional multirate Digital Signal Processing systems by exploiting the parallelism within those applications. To systematically exploit the parallelism within the multidimensional multirate DSP algorithms, we develop novel transformations including (1) nonlinear I/O data space transforms, (2) intercalation transforms, and (3) multidimensional multirate unfolding transforms. These transformations are applied to the algorithms leading to systematic methodologies in high-performance architectural designs. With the novel design methodologies, we develop several architectures with parallel and distributed processing features for implementing multidimensional multirate applications. Experimental results have shown that those architectures are much more efficient in terms of execution time and/or hardware cost compared with existing hardware implementations

Modelling departure time and mode choice

As a result of increasing road congestion and road pricing, modelling the temporal response of travellers to transport policy interventions has rapidly emerged as a major issue in many practical transport planning studies. A substantial body of research is therefore being carried out to understand the complexities involved in modelling time of day choice. These models are contributing substantially to our understanding of how travellers make time-of-day decisions (Hess et al, 2004; de Jong et al, 2003). These models, however, tend to be far too complex and far too data intensive to be of use for application in large-scale modelling forecasting systems, where socio-economic detail is limited and detailed scheduling information is rarely available. Moreover, model systems making use of the some of the latest analytical structures, such as Mixed Logit, are generally inapplicable in practical planning, since they rely on computer-intensive simulation in application just as well as in estimation. The aim of this paper, therefore, is to describe the development of time-period choice models which are suitable for application in large-scale modelling forecasting systems. Large-scale practical planning models often rely on systems of nested logit models, which can incorporate many of the most important interactions that are present in the complex models but which have low enough run-times to allow them to be used for practical planning. In these systems, temporal choice is represented as the choice between a finite set of discrete alternatives, represented by mutually exclusive time-periods that are obtained by aggregation of the actual observed continuous time values. The issues that face modellers are then: -how should the time periods be defined, and in particular how long should they be? -how should the choices of time periods be related to each other, e.g. is the elasticity for shorter shifts greater than for longer shifts? -how should time period choice be placed in the model system relative to other choices, such as that of the mode of travel? These questions cannot be answered on a purely theoretical basis but require the analysis of empirical data. However, there is not a great deal of data available on the relevant choices. The time period models described in the paper are developed from three related stated preference (SP) studies undertaken over the past decade in the United Kingdom and the Netherlands. Because of the complications involved with using advanced models in large-scale modelling forecasting systems, the model structures are limited to nested logit models. Two different tree structures are explored in the analysis, nesting mode above time period choice or time period choice above mode. The analysis examines how these structures differ by data set, purpose of travel and time period specification. Three time period specifications were tested, dividing the 24-hour day into: -twenty-four 1-hour periods; -five coarse time-periods; -sixteen 15-minute morning-peak periods, and two coarse pre-peak and post-peak periods. In each case, the time periods are used to define both the outbound and the return trip timings. The analysis shows that, with a few exceptions, the nested models outperform the basic Multinomial Logit structures, which operate under the assumption of equal substitution patterns across alternatives. With a single exception, the nested models in turn show higher substitution between alternative time periods than between alternative modes, showing that, for all the time period lengths studied, travellers are more sensitive to transport levels of service in their choice of departure time than in choice of mode. The advantages of the nesting structures are especially pronounced in the 1-hour and 15-minute models, while, in the coarse time-period models, the MNL model often remains the preferred structure; this is a clear effect of the broader time-periods, and the consequently lower substitution between time-periods.

Fast algorithms for retiming large digital circuits

The increasing complexity of VLSI systems and shrinking time to market requirements demand good optimization tools capable of handling large circuits. Retiming is a powerful transformation that preserves functionality, and can be used to optimize sequential circuits for a wide range of objective functions by judiciously relocating the memory elements. Leiserson and Saxe, who introduced the concept, presented algorithms for period optimization (minperiod retiming) and area optimization (minarea retiming). The ASTRA algorithm proposed an alternative view of retiming using the equivalence between retiming and clock skew optimization;The first part of this thesis defines the relationship between the Leiserson-Saxe and the ASTRA approaches and utilizes it for efficient minarea retiming of large circuits. The new algorithm, Minaret, uses the same linear program formulation as the Leiserson-Saxe approach. The underlying philosophy of the ASTRA approach is incorporated to reduce the number of variables and constraints in this linear program. This allows minarea retiming of circuits with over 56,000 gates in under fifteen minutes;The movement of flip-flops in control logic changes the state encoding of finite state machines, requiring the preservation of initial (reset) states. In the next part of this work the problem of minimizing the number of flip-flops in control logic subject to a specified clock period and with the guarantee of an equivalent initial state, is formulated as a mixed integer linear program. Bounds on the retiming variables are used to guarantee an equivalent initial state in the retimed circuit. These bounds lead to a simple method for calculating an equivalent initial state for the retimed circuit;The transparent nature of level sensitive latches enables level-clocked circuits to operate faster and require less area. However, this transparency makes the operation of level-clocked circuits very complex, and optimization of level-clocked circuits is a difficult task. This thesis also presents efficient algorithms for retiming large level-clocked circuits. The relationship between retiming and clock skew optimization for level-clocked circuits is defined and utilized to develop efficient retiming algorithms for period and area optimization. Using these algorithms a circuit with 56,000 gates could be retimed for minimum period in under twenty seconds and for minimum area in under 1.5 hours

Power and memory optimization techniques in embedded systems design

Embedded systems incur tight constraints on power consumption and memory (which impacts size) in addition to other constraints such as weight and cost. This dissertation addresses two key factors in embedded system design, namely minimization of power consumption and memory requirement. The first part of this dissertation considers the problem of optimizing power consumption (peak power as well as average power) in high-level synthesis (HLS). The second part deals with memory usage optimization mainly targeting a restricted class of computations expressed as loops accessing large data arrays that arises in scientific computing such as the coupled cluster and configuration interaction methods in quantum chemistry. First, a mixed-integer linear programming (MILP) formulation is presented for the scheduling problem in HLS using multiple supply-voltages in order to optimize peak power as well as average power and energy consumptions. For large designs, the MILP formulation may not be suitable; therefore, a two-phase iterative linear programming formulation and a power-resource-saving heuristic are presented to solve this problem. In addition, a new heuristic that uses an adaptation of the well-known force-directed scheduling heuristic is presented for the same problem. Next, this work considers the problem of module selection simultaneously with scheduling for minimizing peak and average power consumption. Then, the problem of power consumption (peak and average) in synchronous sequential designs is addressed. A solution integrating basic retiming and multiple-voltage scheduling (MVS) is proposed and evaluated. A two-stage algorithm namely power-oriented retiming followed by a MVS technique for peak and/or average power optimization is presented. Memory optimization is addressed next. Dynamic memory usage optimization during the evaluation of a special class of interdependent large data arrays is considered. Finally, this dissertation develops a novel integer-linear programming (ILP) formulation for static memory optimization using the well-known fusion technique by encoding of legality rules for loop fusion of a special class of loops using logical constraints over binary decision variables and a highly effective approximation of memory usage

Parallélisme des nids de boucles pour l’optimisation du temps d’exécution et de la taille du code

The real time implementation algorithms always include nested loops which require important execution times. Thus, several nested loop parallelism techniques have been proposed with the aim of decreasing their execution times. These techniques can be classified in terms of granularity, which are the iteration level parallelism and the instruction level parallelism. In the case of the instruction level parallelism, the techniques aim to achieve a full parallelism. However, the loop carried dependencies implies shifting instructions in both side of nested loops. Consequently, these techniques provide implementations with non-optimal execution times and important code sizes, which represent limiting factors when implemented on embedded real-time systems. In this work, we are interested on enhancing the parallelism strategies of nested loops. The first contribution consists of purposing a novel instruction level parallelism technique, called “delayed multidimensional retiming”. It aims to scheduling the nested loops with the minimal cycle period, without achieving a full parallelism. The second contribution consists of employing the “delayed multidimensional retiming” when providing nested loop implementations on real time embedded systems. The aim is to respect an execution time constraint while using minimal code size. In this context, we proposed a first approach that selects the minimal instruction parallelism level allowing the execution time constraint respect. The second approach employs both instruction level parallelism and iteration level parallelism, by using the “delayed multidimensional retiming” and the “loop striping”Les algorithmes des systèmes temps réels incluent de plus en plus de nids de boucles, qui sont caractérisés par un temps d’exécution important. De ce fait, plusieurs démarches de parallélisme des boucles imbriquées ont été proposées dans l’objectif de réduire leurs temps d’exécution. Ces démarches peuvent être classifiées selon deux niveaux de granularité : le parallélisme au niveau des itérations et le parallélisme au niveau des instructions. Dans le cas du deuxième niveau de granularité, les techniques visent à atteindre un parallélisme total des instructions appartenant à une même itération. Cependant, le parallélisme est contraint par les dépendances des données inter-itérations ce qui implique le décalage des instructions à travers les boucles imbriquées, provocant ainsi une augmentation du code proportionnelle au niveau du parallélisme. Par conséquent, le parallélisme total au niveau des instructions des nids de boucles engendre des implémentations avec des temps d’exécution non-optimaux et des tailles du code importantes. Les travaux de cette thèse s’intéressent à l’amélioration des stratégies de parallélisme des nids de boucles. Une première contribution consiste à proposer une nouvelle technique de parallélisme au niveau des instructions baptisée « retiming multidimensionnel décalé ». Elle vise à ordonnancer les nids de boucles avec une période de cycle minimale, sans atteindre un parallélisme total. Une deuxième contribution consiste à mettre en pratique notre technique dans le contexte de l’implémentation temps réel embarquée des nids de boucles. L’objectif est de respecter la contrainte du temps d’exécution tout en utilisant un code de taille minimale. Dans ce contexte, nous avons proposé une première démarche d’optimisation qui consiste à utiliser notre technique pour déterminer le niveau parallélisme minimal. Par la suite, nous avons décrit une deuxième démarche permettant de combiner les parallélismes au niveau des instructions et au niveau des itérations, en utilisant notre technique et le « loop striping