190 research outputs found

    Instantaneous Transitions in Esterel

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    Esterel is an imperative synchronous programming language for the specification of deterministic concurrent reactive systems. While providing the usual control-flow constructs—sequences, loops, conditionals, and exceptions—its lack of a goto instruction makes the programming of arbitrary finite state machines awkward and hinders the design of source-to-source program transformations. We previously introduced to Esterel a non-instantaneous gotopause instruction, which prevents the synchronous execution of code before and code after the transition. Here, we tackle instantaneous transitions. Concurrency demands we assign scopes and priorities to gotos, so we extend Esterel's exception handling mechanism to allow exception handlers in arbitrary locations. We advocate for and formalize the resulting language. We observe that instantaneous gotos complement but do not replace non-instantaneous gotopauses

    Optimizing Sequential Cycles Through Shannon Decomposition and Retiming

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    Optimizing sequential cycles is essential for many types of high-performance circuits, such as pipelines for packet processing. Retiming is a powerful technique for speeding pipelines, but it is stymied by tight sequential cycles. Designers usually attack such cycles by manually combining Shannon decomposition with retiming-effectively a form of speculation-but such manual decomposition is error prone. We propose an efficient algorithm that simultaneously applies Shannon decomposition and retiming to optimize circuits with tight sequential cycles. While the algorithm is only able to improve certain circuits (roughly half of the benchmarks we tried), the performance increase can be dramatic (7%-61%) with only a modest increase in area (1%-12%). The algorithm is also fast, making it a practical addition to a synthesis flow

    GLB: Lifeline-based Global Load Balancing library in X10

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    We present GLB, a programming model and an associated implementation that can handle a wide range of irregular paral- lel programming problems running over large-scale distributed systems. GLB is applicable both to problems that are easily load-balanced via static scheduling and to problems that are hard to statically load balance. GLB hides the intricate syn- chronizations (e.g., inter-node communication, initialization and startup, load balancing, termination and result collection) from the users. GLB internally uses a version of the lifeline graph based work-stealing algorithm proposed by Saraswat et al. Users of GLB are simply required to write several pieces of sequential code that comply with the GLB interface. GLB then schedules and orchestrates the parallel execution of the code correctly and efficiently at scale. We have applied GLB to two representative benchmarks: Betweenness Centrality (BC) and Unbalanced Tree Search (UTS). Among them, BC can be statically load-balanced whereas UTS cannot. In either case, GLB scales well-- achieving nearly linear speedup on different computer architectures (Power, Blue Gene/Q, and K) -- up to 16K cores
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