ASAM : Automatic Architecture Synthesis and Application Mapping; dl. 3.2: Instruction set synthesis

No abstract

Rapid evaluation of custom instruction selection approaches with FPGA estimation

The main aim of this article is to demonstrate that a fast and accurate FPGA estimation engine is indispensable in design flows for custom instruction (template) selection. The need for a FPGA estimation engine stems from the difficulty in predicting the FPGA performance measures of selected custom instructions. We will present a FPGA estimation technique that partitions the high-level representation of custom instructions into clusters based on the structural organization of the target FPGA, while taking into account general logic synthesis principles adopted by FPGA tools. In this work, we have evaluated a widely used graph covering algorithm with various heuristics for custom instruction selection. In addition, we present an algorithm called Refined Largest Fit First (RLFF) that relies on a graph covering heuristic to select non-overlapping superset templates, which typically incorporate frequently used basic templates. The initial solution is further refined by considering overlapping templates that were ignored previously to see if their introduction could lead to higher performance. While RLFF provides the most efficient cover compared to the ILP method and other graph covering heuristics, FPGA estimation results reveals that RLFF leads to the worst performance in certain applications. It is therefore a worthy proposition to equip design flows with accurate FPGA estimation in order to rapidly determine the most profitable custom instruction approach for a given application.</jats:p

Algoritmos para alocação de recursos em arquiteturas reconfiguraveis

Orientador: Guido Costa Souza de AraujoTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Pesquisas recentes na área de arquiteturas reconfiguráveis mostram que elas oferecem um desempenho melhor que os processadores de propósito geral (GPPs - General Purpose Processors), aliado a uma maior flexibilidade que os ASICs (Application Specific Integrated Circuits). Uma mesma arquitetura recongurável pode ser adaptada para implementar aplicações diferentes, permitindo a especialização do hardware de acordo com a demanda computacional da aplicação. Neste trabalho, nos estudamos o projeto de sistemas dedicados baseado em uma arquitetura reconfigurável. Adotamos a abordagem de extensão do conjunto de instruções, na qual o conjunto de instruções de um GPP e acrescido de instruções especializadas para uma aplicação. Estas instruções correspondem a trechos da aplicação e são executadas em um datapath dinamicamente recongurável, adicionado ao hardware do GPP. O tema central desta tese e o problema de compartilhamento de recursos no projeto do datapath reconfigurável. Dado que os trechos da aplicação são modelados como grafos de luxo de dados e controle (Control/Data-Flow Graphs ¿ CDFGs), o problema de combinação de CDFGs consiste em projetar um datapath reconfigurável com área mínima. Nos apresentamos uma demonstração de que este problema e NP-completo. Nossas principais contribuições são dois algoritmos heurísticos para o problema de combinação de CDFGs. O primeiro tem o objetivo de minimizar a área das interconexões do datapath reconfigurável, enquanto que o segundo visa a minimização da área total. Avaliações experimentais mostram que nossa primeira heurística resultou em uma redução media de 26,2% na área das interconexões, em relação ao método mais utilizado na literatura. O erro máximo de nossas soluções foi em media 4,1% e algumas soluções ótimas foram obtidas. Nosso segundo algoritmo teve tempos de execução comparáveis ao método mais rápido conhecido, obtendo uma redução media de 20% na área. Em relação ao melhor método para área conhecido, nossa heurística produziu áreas um pouco menores, alcançando um speed up médio de 2500. O algoritmo proposto também produziu áreas menores, quando comparado a uma ferramenta de síntese comercialAbstract: Recent work in reconfigurable architectures shows that they ofter a better performance than general purpose processors (GPPs), while offering more exibility than ASICs (Application Specific Integrated Circuits). A reconfigurable architecture can be adapted to implement different applications, thus allowing the specialization of the hardware according to the computational demands. In this work we describe an embedded systems project based on a reconfigurable architecture. We adopt an instruction set extension technique, where specialized instructions for an application are included into the instruction set of a GPP. These instructions correspond to sections of the application, and are executed in a dynamically reconfigurable datapath, added to the GPP's hardware. The central focus of this theses is the resource sharing problem in the design of reconfigurable datapaths. Since the application sections are modeled as control/data-ow graphs (CDFGs), the CDFG merging problem consists in designing a reconfigurable datapath with minimum area. We prove that this problem is NP-complete. Our main contributions are two heuristic algorithms to the CDFG merging problem. The first has the goal of minimizing the reconfigurable datapath interconnection area, while the second minimizes its total area. Experimental evaluation showed that our first heuristic produced an average 26.2% area reduction, with respect to the most used method. The maximum error of our solutions was on average 4.1%, and some optimal solutions were found. Our second algorithm approached, in execution times, the fastest previous solution, and produced datapaths with an average area reduction of 20%. When compared to the best known area solution, our approach produced slightly better areas, while achieving an average speedup of 2500. The proposed algorithm also produced smaller areas, when compared to an industry synthesis toolDoutoradoDoutor em Ciência da Computaçã

Accuracy-Guaranteed Fixed-Point Optimization in Hardware Synthesis and Processor Customization

RÉSUMÉ De nos jours, le calcul avec des nombres fractionnaires est essentiel dans une vaste gamme d’applications de traitement de signal et d’image. Pour le calcul numérique, un nombre fractionnaire peut être représenté à l’aide de l’arithmétique en virgule fixe ou en virgule flottante. L’arithmétique en virgule fixe est largement considérée préférable à celle en virgule flottante pour les architectures matérielles dédiées en raison de sa plus faible complexité d’implémentation. Dans la mise en œuvre du matériel, la largeur de mot attribuée à différents signaux a un impact significatif sur des métriques telles que les ressources (transistors), la vitesse et la consommation d'énergie. L'optimisation de longueur de mot (WLO) en virgule fixe est un domaine de recherche bien connu qui vise à optimiser les chemins de données par l'ajustement des longueurs de mots attribuées aux signaux. Un nombre en virgule fixe est composé d’une partie entière et d’une partie fractionnaire. Il y a une limite inférieure au nombre de bits alloués à la partie entière, de façon à prévenir les débordements pour chaque signal. Cette limite dépend de la gamme de valeurs que peut prendre le signal. Le nombre de bits de la partie fractionnaire, quant à lui, détermine la taille de l'erreur de précision finie qui est introduite dans les calculs. Il existe un compromis entre la précision et l'efficacité du matériel dans la sélection du nombre de bits de la partie fractionnaire. Le processus d'attribution du nombre de bits de la partie fractionnaire comporte deux procédures importantes: la modélisation de l'erreur de quantification et la sélection de la taille de la partie fractionnaire. Les travaux existants sur la WLO ont porté sur des circuits spécialisés comme plate-forme cible. Dans cette thèse, nous introduisons de nouvelles méthodologies, techniques et algorithmes pour améliorer l’implémentation de calculs en virgule fixe dans des circuits et processeurs spécialisés. La thèse propose une approche améliorée de modélisation d’erreur, basée sur l'arithmétique affine, qui aborde certains problèmes des méthodes existantes et améliore leur précision. La thèse introduit également une technique d'accélération et deux algorithmes semi-analytiques pour la sélection de la largeur de la partie fractionnaire pour la conception de circuits spécialisés. Alors que le premier algorithme suit une stratégie de recherche progressive, le second utilise une méthode de recherche en forme d'arbre pour l'optimisation de la largeur fractionnaire. Les algorithmes offrent deux options de compromis entre la complexité de calcul et le coût résultant. Le premier algorithme a une complexité polynomiale et obtient des résultats comparables avec des approches heuristiques existantes. Le second algorithme a une complexité exponentielle, mais il donne des résultats quasi-optimaux par rapport à une recherche exhaustive. Cette thèse propose également une méthode pour combiner l'optimisation de la longueur des mots dans un contexte de conception de processeurs configurables. La largeur et la profondeur des blocs de registres et l'architecture des unités fonctionnelles sont les principaux objectifs ciblés par cette optimisation. Un nouvel algorithme d'optimisation a été développé pour trouver la meilleure combinaison de longueurs de mots et d'autres paramètres configurables dans la méthode proposée. Les exigences de précision, définies comme l'erreur pire cas, doivent être respectées par toute solution. Pour faciliter l'évaluation et la mise en œuvre des solutions retenues, un nouvel environnement de conception de processeur a également été développé. Cet environnement, qui est appelé PolyCuSP, supporte une large gamme de paramètres, y compris ceux qui sont nécessaires pour évaluer les solutions proposées par l'algorithme d'optimisation. L’environnement PolyCuSP soutient l’exploration rapide de l'espace de solution et la capacité de modéliser différents jeux d'instructions pour permettre des comparaisons efficaces.----------ABSTRACT Fixed-point arithmetic is broadly preferred to floating-point in hardware development due to the reduced hardware complexity of fixed-point circuits. In hardware implementation, the bitwidth allocated to the data elements has significant impact on efficiency metrics for the circuits including area usage, speed and power consumption. Fixed-point word-length optimization (WLO) is a well-known research area. It aims to optimize fixed-point computational circuits through the adjustment of the allocated bitwidths of their internal and output signals. A fixed-point number is composed of an integer part and a fractional part. There is a minimum number of bits for the integer part that guarantees overflow and underflow avoidance in each signal. This value depends on the range of values that the signal may take. The fractional word-length determines the amount of finite-precision error that is introduced in the computations. There is a trade-off between accuracy and hardware cost in fractional word-length selection. The process of allocating the fractional word-length requires two important procedures: finite-precision error modeling and fractional word-length selection. Existing works on WLO have focused on hardwired circuits as the target implementation platform. In this thesis, we introduce new methodologies, techniques and algorithms to improve the hardware realization of fixed-point computations in hardwired circuits and customizable processors. The thesis proposes an enhanced error modeling approach based on affine arithmetic that addresses some shortcomings of the existing methods and improves their accuracy. The thesis also introduces an acceleration technique and two semi-analytical fractional bitwidth selection algorithms for WLO in hardwired circuit design. While the first algorithm follows a progressive search strategy, the second one uses a tree-shaped search method for fractional width optimization. The algorithms offer two different time-complexity/cost efficiency trade-off options. The first algorithm has polynomial complexity and achieves comparable results with existing heuristic approaches. The second algorithm has exponential complexity but achieves near-optimal results compared to an exhaustive search. The thesis further proposes a method to combine word-length optimization with application-specific processor customization. The supported datatype word-length, the size of register-files and the architecture of the functional units are the main target objectives to be optimized. A new optimization algorithm is developed to find the best combination of word-length and other customizable parameters in the proposed method. Accuracy requirements, defined as the worst-case error bound, are the key consideration that must be met by any solution. To facilitate evaluation and implementation of the selected solutions, a new processor design environment was developed. This environment, which is called PolyCuSP, supports necessary customization flexibility to realize and evaluate the solutions given by the optimization algorithm. PolyCuSP supports rapid design space exploration and capability to model different instruction-set architectures to enable effective compari

Custom-Instruction Synthesis for Extensible-Processor Platforms

Efficiency and flexibility are critical, but often conflicting, design goals in embedded system design. The recent emergence of extensible processors promises a favorable tradeoff between efficiency and flexibility, while keeping design turnaround times short. Current extensible processor design flows automate several tedious tasks, but typically require designers to manually select the parts of the program that are to be implemented as custom instructions. In this work, we describe an automatic methodology to select custom instructions to augment an extensible processor, in order to maximize its efficiency for a given application program. We demonstrate that the number of custom instruction candidates grows rapidly with program size, leading to a large design space, and that the quality (speedup) of custom instructions varies significantly across this space, motivating the need for the proposed flow. Our methodology features cost functions to guide the custom instruction selection process, as well as static and dynamic pruning techniques to eliminate inferior parts of the design space from consideration. Furthermore, we employ a two-stage process, wherein a limited number of promising instruction candidates are first short-listed using efficient selection criteria, and then evaluated in more detail through cycle-accurate instruction set simulation and synthesis of the corresponding hardware, to identify the custom instruction combinations that result in the highest program speedup or maximize speedup under a given area constraint. We have evaluated the proposed techniques using a state-of-the-art extensible processor platform, in the context of a commercial design flow. Experiments with several benchmark programs indicate that custom processors synthesized using automa..

RISPP: A Run-time Adaptive Reconfigurable Embedded Processor

This Ph.D. thesis describes a new approach for adaptive processors using a reconfigurable fabric (embedded FPGA) to implement application-specific accelerators. A novel modular Special Instruction composition is presented along with a run-time system that exploits the provided adaptivity. The approach was simulated and prototyped using and FPGA. Comparisons with state-of-the-art appl.-specific and reconf. processors demonstrate significant improvements according the performance and efficiency

Fast Instruction Set Customization

This paper proposes an approach to tune embedded processor datapaths toward a specific application, so as to maximize the application performance. We customize the computation capabilities of a base processor, by extending its instruction set to include custom operations which are implemented as new specialized functional units. We describe an automatic methodology to select the custom instructions from the given application code, in a way that there is no need of compensation code or other modifications in the application, simplifying the code generation. By using the ArchC architecture description language, fast compilation and simulation of the resulting customized processor code are achieved, considerably reducing the turnaround time required to evaluate the best set of custom operations. Experimental results show that our framework provides large performance improvements (up to 3.6 times), when compared to the base general-purpose processor, while significantly speeding up the design process.5358Arnold, M., Corporaal, H., Designing domain-specific processors (2001) CODES, pp. 61-66Atasu, K., Pozzi, L., Ienne, P., Automatic application-specific instruction-set extensions under microarchitectural constraints (2003) DAC, pp. 256-261Brisk, P., Kaplan, A., Kastner, R., Sarrafzadeh, M., Instruction generation and regularity extraction for reconfigurable processors (2002) CASES, pp. 262-269Cheung, N., Parameswaran, S., Henkel, J., INSIDE: Instruction selection/identification & design exploration for extensible processors (2003) ICCAD, pp. 291-297Choi, H., Kim, J., Yoon, C., Park, I., Hwang, S., Kyung, C., Synthesis of application specific instructions for embedded DSP software (1999) IEEE Transactions on Computers, 48 (6), pp. 603-614Clark, N., Zhong, H., Tang, W., Mahlke, S., Automatic design of application specific instruction set extensions through dataflow graph exploration (2003) International Journal of Parallel Programming, 31 (6), pp. 429-449Garey, M., Johnson, D., (1979) Computers and Intractability -A Guide to the Theory of NP-completeness, , Freeman and COGoodwin, D., Petkov, D., Automatic generation of application specific processors (2003) CASES, pp. 137-147Guthaus, M., Ringenberg, J., Ernst, D., Austin, T., Mudge, T., Brown, R., Mibench: A free, commercially representative embedded benchmark suite (2001) WWC, pp. 3-14Hennessy, J., Patterson, D., Goldberg, D., (2002) Computer Architecture: A Quantitative Approach, , Morgan Kaufmann PublishersHuang, I., Despain, A., Synthesis of application specific instruction sets (1995) IEEE TCAD, 14 (6), pp. 663-675Kastner, R., Kaplan, A., Memik, S.O., Bozorgzadeh, E., Instruction generation for hybrid reconfigurable systems (2002) ACM TODAES, 7 (4), pp. 605-627La Rosa, A., Lavagno, L., Passerone, C., Hardware/software design space exploration for a reconfigurable processor (2003) DATE, pp. 570-575Lee, C., Potkonjak, M., Mangione-Smith, W., MediaBench: A tool for evaluating and synthesizing multimedia and communication systems (1997) MICRO, pp. 330-335Muchnick, S., (1997) Advanced Compiler Design and Implementation, , Morgan Kaufmann PublishersRigo, S., Araujo, G., Bartholomeu, M., Azevedo, R., ArchC: A SystemC-based architecture description language (2004) 16th Symposium on Computer Architecture and High Performance Computing (SBAC), , http://www.archc.org, Accepted for publication at theStallman, R., (2002) GNU Compiler Collection InternalsSun, F., Ravi, S., Raghunathan, A., Jha, N., Custom-instruction synthesis for extensible-processor platforms (2004) IEEE TCAD, 23 (2), pp. 216-228Van Praet, J., Goossens, G., Lanneer, D., De Man, H., Instruction set definition and instruction selection for ASIPs (1994) Proceedings of the 7th International Symposium on High-level Synthesis, pp. 11-1