Silicon compilation

Silicon compilation is a term used for many different purposes. In this paper we define silicon compilation as a mapping from some higher level description into layout. We define the basic issues in structural and behavioral silicon compilation and some possible solutions to those issues. Finally, we define the concept of an intelligent silicon compiler in which the compiler evaluates the quality of the generated design and attempts to improve it if it is not satisfactory

Regular Datapaths on Field-Programmable Gate Arrays

Field-Programmable Gate Arrays (FPGAs) are a recent kind of programmable logic device. They allow the implementation of integrated digital electronic circuits without requiring the complex optical, chemical and mechanical processes used in a conventional chip fabrication. FPGAs can be embedded in traditional system designflows to perform prototyping and emulation tasks. In addition, they also enable novel applications such as configurable computers with hardware dynamically adaptable to a specific problem. The growing chip capacity now allows even the implementation of CPUs and DSPs on single FPGAs. However, current design automation tools trace their roots to times of very limited FPGA sizes, and are primarily optimized for the implementation of random glue logic. The wide datapaths common to CPUs and DSPs are only processed with reduced performance. This thesis presents Structured Design Implementation (SDI), a suite of specialized tools coordinated by a common strategy, which aims to efficiently map even larger regular datapaths to FPGAs. In all steps, regularity is preserved whenever possible, or restored after disruptive operations were required. The circuits are composed from parametrizable modules providing a variety of logical, arithmetical and storage functions. For each module, multiple target FPGA-specific implementation alternatives may be generated in both gatelevel netlist and layout views. A floorplanner based on a genetic algorithm is then used to simultaneously choose an actual implementation from the set of alternatives for each module, and to arrange the selected module implementations in a linear placement. The floorplanning operation optimizes for short routing delays, high routability, and fit into the target FPGA.Field-Programmable Gate-Arrays (FPGAs) sind eine noch junge Art von programmierbaren Logikbausteinen. Sie erlauben die Implementierung von integrierten Digitalschaltungen ohne die komplizierten optischen, chemischen und mechanischen Prozesse, die normalerweise für die Chipfertigung erforderlich sind. FPGAs können im Rahmen konventioneller Entwurfsmethoden zu Emulationszwecken und Prototyp-Aufbauten herangezogen werden. Sie erlauben aber auch völlig neue Anwendungen wie rekonfigurierbare Computer, deren Hardware dynamisch an ein spezielles Problem angepaßt werden kann. Die gewachsene Chip-Kapazität erlaubt nun sogar die Implementierung von CPUs und digitalen Signalprozessoren (DSPs) auf einem einzelnen FPGA. Die Leistungsfähigkeit der entstandenen Schaltungen wird jedoch durch die zur Zeit erhältlichen CAD-Werkzeuge limitiert, da diese noch auf stark beschränkte FPGA-Größen ausgerichtet sind und primär der platzsparenden Verarbeitung unregelmäßiger Logik dienen. Die breiten Datenpfade in Bit-Slice-Struktur, die den Kern vieler CPUs und DSPs darstellen, werden nur suboptimal behandelt. Diese Arbeit stellt Structured Design Implementation (SDI) vor, ein System von spezialisierten CAD-Werkzeugen, die auch größere reguläre Datenpfade effizient auf FPGAs abbilden. In allen Verarbeitungsschritten wird dabei die bestehende Regularität soweit wie möglich erhalten oder nach regularitätsvernichtenden Operationen wiederhergestellt. Zur Schaltungseingabe steht eine Bibliothek von allgemeinen Modulen aus den Bereichen Logik, Arithmetik und Speicherung bereit. Diese können durch Belegung verschiedener Parameter wie Bit-Breiten und Datentypen an aktuelle Anforderungen angepaßt werden

Modeling of a hardware VLSI placement system: Accelerating the Simulated Annealing algorithm

An essential step in the automation of electronic design is the placement of the physical components on the target semiconductor die. The placement step presents the opportunity to reduce costs in terms of wire length and performance degradation; however it is compute intensive and is NP-complete in terms of obtaining an optimal solution. As designs have grown in complexity and gate count, obtaining an optimal solution is not feasible due to time to market constraints or sheer compute effort required. Heuristic algorithms allow for efficient but sub-optimal designs to be produced with a reduction in processing time. A widely used algorithm is Simulated Annealing (SA). The goal of this work was to develop a model that would enable an analysis into the feasibility of developing a hardware accelerated placement system which uses SA at its core. The SA heuristic was analyzed for possible improvements in efficiency with focus given to targeting the system for hardware. A solution implementing parallel computing with specialized hardware configurations inside a field programmable gate array (FPGA) was investigated as having the possibility to improve the efficiency of the SA-based algorithm. All supporting subsystems were also described for a hardware accelerated model. A large speedup was analytically shown from both accelerating the critical path of the SA algorithm as well as novel methods of improving SA\u27s efficiency. As data throughput requirements were not included in this work, the results presented may be optimistic for an overall system speedup. However, the results clearly show that future work is warranted in studying the concept of a hardware accelerated placement system