In this paper, we survey the design space of a new class of architec-tures called Grid Processor Architectures (GPAs). These architectures are designed to scale with technology, allowing faster clock rates than conventional architectures while providing superior instruction-level parallelism on traditional workloads and high performance across a range of application classes. A GPA consists of an array of ALUs, each with limited control, connected by a thin operand network. Pro-grams are executed by mapping blocks of statically scheduled instruc-tions to the ALU array and executing them dynamically in dataflow or-der This organization enables the critical paths of instruction blocks to be executed on chains of ALUs without transmitting temporary val-ues back to the register file, avoiding most of the large, unscalable structures that limit the scalability of conventional architectures. Fi-nally, we present simulation results of a preliminary design, the GPA-1. With a half-cycle routing delay, we obtain performance roughly equal to an ideal 8-way, 512-entry window superscalar core. With no inter-ALU delay, perfect memory, and perfect branch prediction, the 1PC of the GPA-1 is more than twice that of the ideal superscalar core, achieving an average of 11 IPC across nine SPEC CPU2000 and Mediabench benchmarks.
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Nagarajan et al. (2001) studied this question.
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