SLAP: A Split Latency Adaptive VLIW pipeline architecture which enables on-the-fly variable SIMD vector-length release_j6wol5bddbhwddwhac5rll54rq

by Ashish Shrivastava and Alan Gatherer and Tong Sun and Sushma Wokhlu and Alex Chandra

Released as a article .

2021  

Abstract

Over the last decade the relative latency of access to shared memory by multicore increased as wire resistance dominated latency and low wire density layout pushed multiport memories farther away from their ports. Various techniques were deployed to improve average memory access latencies, such as speculative pre-fetching and branch-prediction, often leading to high variance in execution time which is unacceptable in real time systems. Smart DMAs can be used to directly copy data into a layer1 SRAM, but with overhead. The VLIW architecture, the de facto signal processing engine, suffers badly from a breakdown in lockstep execution of scalar and vector instructions. We describe the Split Latency Adaptive Pipeline (SLAP) VLIW architecture, a cache performance improvement technology that requires zero change to object code, while removing smart DMAs and their overhead. SLAP builds on the Decoupled Access and Execute concept by 1) breaking lockstep execution of functional units, 2) enabling variable vector length for variable data level parallelism, and 3) adding a novel triangular load mechanism. We discuss the SLAP architecture and demonstrate the performance benefits on real traces from a wireless baseband system (where even the most compute intensive functions suffer from an Amdahls law limitation due to a mixture of scalar and vector processing).
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Date   2021-02-26
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arXiv  2102.13301v1
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