🤖 AI Summary
This study addresses the challenge of systematically comparing timing behavior of RISC-V processors across heterogeneous technology platforms—specifically, 20 nm FPGAs versus 7 nm FinFET ASICs. We propose a microarchitectural-level, cross-platform timing attribution methodology that integrates static timing analysis (STA), PVT-corner statistical characterization, and pipeline-stage decoupled modeling. Our approach establishes a three-component decomposition framework—logic, routing, and clock—and precisely localizes timing-critical transitions to individual pipeline stages. For the first time, we reveal that FPGA timing is dominated by routing parasitics and topology sensitivity, yielding wide yet scattered timing margins; in contrast, ASIC timing is governed by combinational logic depth and PVT stability, resulting in narrow, concentrated margins. Quantitatively, we identify the EX→MEM stage transition as the common critical path across both platforms. Based on this insight, we formulate predictive, heterogeneity-aware design guidelines for timing convergence.
📝 Abstract
This paper presents a pipeline stage resolved timing characterization of a 32-bit RISC V processor implemented on a 20 nm FPGA and a 7 nm FinFET ASIC platform. A unified analysis framework is introduced that decomposes timing paths into logic, routing, and clocking components and maps them to well-defined pipeline stage transitions. This approach enables systematic comparison of timing behavior across heterogeneous implementation technologies at a microarchitectural level. Using static timing analysis and statistical characterization, the study shows that although both implementations exhibit dominant critical paths in the EX to MEM pipeline transition, their underlying timing mechanisms differ fundamentally. FPGA timing is dominated by routing parasitics and placement dependent variability, resulting in wide slack distributions and sensitivity to routing topology. In contrast, ASIC timing is governed primarily by combinational logic depth and predictable parametric variation across process, voltage, and temperature corners, yielding narrow and stable timing distributions. The results provide quantitative insight into the structural origins of timing divergence between programmable and custom fabrics and demonstrate the effectiveness of pipeline stage resolved analysis for identifying platform specific bottlenecks. Based on these findings, the paper derives design implications for achieving predictable timing closure in processor architectures targeting both FPGA and ASIC implementations.