IEICE TRANSACTIONS on Fundamentals
Proposal of Metrics for SSTA Accuracy Evaluation
Summary :
With the recent advance of process technology shrinking, process parameter variation has become one of the major issues in SoC designs, especially for timing convergence. Recently, Statistical Static Timing Analysis (SSTA) has been proposed as a promising solution to consider the process parameter variation but it has not been widely used yet. For estimating the delay yield, designers have to know and understand the accuracy of SSTA. However, the accuracy has not been thoroughly studied from a practical point of view. This paper proposes two metrics to measure the pessimism/optimism of SSTA; the first corresponds to yield estimation error, and the second examines delay estimation error. We apply the metrics for a problem which has been widely discussed in SSTA community, that is, normal-distribution approximation of max operation. We also apply the proposed metrics for benchmark circuits and discuss about a potential problem originating from normal-distribution approximation. Our metrics indicate that the appropriateness of the approximation depends on not only given input distributions but also the target yield of the product, which is an important message for SSTA users.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.4 pp.808-814
- Publication Date
- 2007/04/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e90-a.4.808
- Type of Manuscript
- Special Section PAPER (Special Section on Selected Papers from the 19th Workshop on Circuits and Systems in Karuizawa)
- Category
Authors
Hiroyuki KOBAYASHI
Nobuto ONO
Takashi SATO
Jiro IWAI
Hidenari NAKASHIMA
Takaaki OKUMURA
Masanori HASHIMOTO
Keyword
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Hiroyuki KOBAYASHI, Nobuto ONO, Takashi SATO, Jiro IWAI, Hidenari NAKASHIMA, Takaaki OKUMURA, Masanori HASHIMOTO, "Proposal of Metrics for SSTA Accuracy Evaluation" in IEICE TRANSACTIONS on Fundamentals,
vol. E90-A, no. 4, pp. 808-814, April 2007, doi: 10.1093/ietfec/e90-a.4.808.
Abstract: With the recent advance of process technology shrinking, process parameter variation has become one of the major issues in SoC designs, especially for timing convergence. Recently, Statistical Static Timing Analysis (SSTA) has been proposed as a promising solution to consider the process parameter variation but it has not been widely used yet. For estimating the delay yield, designers have to know and understand the accuracy of SSTA. However, the accuracy has not been thoroughly studied from a practical point of view. This paper proposes two metrics to measure the pessimism/optimism of SSTA; the first corresponds to yield estimation error, and the second examines delay estimation error. We apply the metrics for a problem which has been widely discussed in SSTA community, that is, normal-distribution approximation of max operation. We also apply the proposed metrics for benchmark circuits and discuss about a potential problem originating from normal-distribution approximation. Our metrics indicate that the appropriateness of the approximation depends on not only given input distributions but also the target yield of the product, which is an important message for SSTA users.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.4.808/_p
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@ARTICLE{e90-a_4_808,
author={Hiroyuki KOBAYASHI, Nobuto ONO, Takashi SATO, Jiro IWAI, Hidenari NAKASHIMA, Takaaki OKUMURA, Masanori HASHIMOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Proposal of Metrics for SSTA Accuracy Evaluation},
year={2007},
volume={E90-A},
number={4},
pages={808-814},
abstract={With the recent advance of process technology shrinking, process parameter variation has become one of the major issues in SoC designs, especially for timing convergence. Recently, Statistical Static Timing Analysis (SSTA) has been proposed as a promising solution to consider the process parameter variation but it has not been widely used yet. For estimating the delay yield, designers have to know and understand the accuracy of SSTA. However, the accuracy has not been thoroughly studied from a practical point of view. This paper proposes two metrics to measure the pessimism/optimism of SSTA; the first corresponds to yield estimation error, and the second examines delay estimation error. We apply the metrics for a problem which has been widely discussed in SSTA community, that is, normal-distribution approximation of max operation. We also apply the proposed metrics for benchmark circuits and discuss about a potential problem originating from normal-distribution approximation. Our metrics indicate that the appropriateness of the approximation depends on not only given input distributions but also the target yield of the product, which is an important message for SSTA users.},
keywords={},
doi={10.1093/ietfec/e90-a.4.808},
ISSN={1745-1337},
month={April},}
Copy
TY - JOUR
TI - Proposal of Metrics for SSTA Accuracy Evaluation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 808
EP - 814
AU - Hiroyuki KOBAYASHI
AU - Nobuto ONO
AU - Takashi SATO
AU - Jiro IWAI
AU - Hidenari NAKASHIMA
AU - Takaaki OKUMURA
AU - Masanori HASHIMOTO
PY - 2007
DO - 10.1093/ietfec/e90-a.4.808
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2007
AB - With the recent advance of process technology shrinking, process parameter variation has become one of the major issues in SoC designs, especially for timing convergence. Recently, Statistical Static Timing Analysis (SSTA) has been proposed as a promising solution to consider the process parameter variation but it has not been widely used yet. For estimating the delay yield, designers have to know and understand the accuracy of SSTA. However, the accuracy has not been thoroughly studied from a practical point of view. This paper proposes two metrics to measure the pessimism/optimism of SSTA; the first corresponds to yield estimation error, and the second examines delay estimation error. We apply the metrics for a problem which has been widely discussed in SSTA community, that is, normal-distribution approximation of max operation. We also apply the proposed metrics for benchmark circuits and discuss about a potential problem originating from normal-distribution approximation. Our metrics indicate that the appropriateness of the approximation depends on not only given input distributions but also the target yield of the product, which is an important message for SSTA users.
ER -
English
