Abstract
In this article, we evaluate the performance scalability of architectures called adaptive processors, which dynamically configure an application-specific pipelined datapath and perform a data-flow streaming execution. Previous works have examined the basics of the following: (1) a computational model that supports the swap-in/out of a partial datapath—namely, a virtual hardware is realized by hardware, without a host processor and its software; (2) an architecture that has shown a minimum pipeline requirement and a minimum component requirement; and (3) the characteristics of the execution phase and a stack shift that realizes the swap-in/out. However, these works did not explore the design space, particularly with respect to the following: (1) the clock cycle time on the adaptive processor, which must depend on a wire delay that is primarily used for the global communication of requests, acknowledgments, acquirements, releases, and so forth, and (2) a revised control system that can handle the out-of-order acknowledgment and in-order acquirement that guarantee the correct datapath configuration with a conditional branch for the configurations. This article explores the scaling of the ALU resources versus pipelining of the wires.
Published Version
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