Measuring and modeling variabilityusing low-cost FPGAs

Abstract

The focus of this paper is to measure and qualify high-level process variation models by measuring variability on FPGAs. Measurements are done with high spatial resolution and demonstrate how the high-resolution data matches two industry test cases. The benefit of such an approach is that several inexpensive FPGAs, which are normally on the leading edge of technologies compared to ASICs, obviate the need of fabricating many custom test chips. Specifically, our evaluation shows how measurements of an Altera Cyclone II FPGA can be used to derive variability models for several 90nm commercial designs such as the Sun Niagara and Intel Pentium D. Even though the FPGAs and commercial processors are produced by different fabs (TSMC, TI, and Intel, respectively), we find the FPGAs to be very useful for predicting variation in the commercial processors.

Gate Characterization Using Singular Value Decomposition: Foundations and Applications

“…The critical importance of GLC resulted in creation of a great variety of conceptually, statistically, and algorithmically different techniques, including: (i) direct measurements methods [11], (ii) field-programmable gate array (FPGA) reconfiguration-based approaches [12][13], (iii) schemes that embed and observe dedicated IC structures and specialized circuity [14], and (iv) non-destructive universal techniques that employ global measurements and calculate scaling factors of each gate by solving a system of equations [15] [16][17] [18].…”