TinySPICE plus: Scaling up statistical SPICE simulations on GPU leveraging shared-memory based sparse matrix solution techniques
Document Type
Conference Proceeding
Publication Date
11-7-2016
Abstract
© 2016 ACM. TinySPICE was a SPICE simulator on GPU developed to achieve dramatic speedups in statistical simulations of small nonlinear circuits, such as standard cell designs and SRAMs. While TinySPICE can perform circuit simulations much faster than traditional SPICE tools for small circuits, it may not be efficient for handling relatively large logic/memory circuit designs due to the embedded dense MNA matrix solver that can result in fast growing memory cost with increasing matrix size. In this work, we present TinySPICE Plus, a full-blown statistical SPICE simulation engine on GPU platform that integrates a highly-optimized shared-memory based sparse matrix solver that is capable of dealing with much larger circuits than TinySPICE while achieving orders of magnitude speedup over traditional CPU-based SPICE simulation engine. Extensive experimental results show that TinySPICE Plus can achieves over 70X speedups for parametric yield analysis of SRAM arrays and variation-aware logic circuit characterizations.
Publication Title
IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Recommended Citation
Han, L.,
&
Feng, Z.
(2016).
TinySPICE plus: Scaling up statistical SPICE simulations on GPU leveraging shared-memory based sparse matrix solution techniques.
IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD,
07-10-November-2016.
http://doi.org/10.1145/2966986.2967081
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/12567