Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Raviv Gal"'
Publikováno v:
IEEE Design & Test. 40:5-7
Publikováno v:
Frontiers of Quality Electronic Design (QED) ISBN: 9783031163432
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac0f8fde726da7192139dbab32eb484c
https://doi.org/10.1007/978-3-031-16344-9_5
https://doi.org/10.1007/978-3-031-16344-9_5
Publikováno v:
Machine Learning Applications in Electronic Design Automation ISBN: 9783031130731
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9bbdc418ce58ffe5dc7113651d5f5379
https://doi.org/10.1007/978-3-031-13074-8_14
https://doi.org/10.1007/978-3-031-13074-8_14
Publikováno v:
IEEE Design & Test. 38:97-99
The first ACM/IEEE Workshop on Machine Learning for CAD (MLCAD) was held on September 2–4, 2020 in Canmore, AB, Canada. The location at the entrance to Banff National Park maintained a long tradition of mountain locations for technical meetings ( F
Publikováno v:
MLCAD
In computer aided design (CAD), a core task is to optimize the parameters of noisy simulations. Derivative free optimization (DFO) methods are the most common choice for this task. In this paper, we show how four DFO methods, specifically implicit fi
Publikováno v:
DATE
We present AS-CDG, a novel automatic scalable system for data-driven coverage-directed generation. The goal of AS-CDG is to find the test templates that maximize the probability of hitting uncovered events. The system contains two phases, one for a c
Publikováno v:
MLCAD
Identifying large and important coverage holes is a time-consuming process that requires expertise in the design and its verification environment. This paper describes a novel machine learning-based technique for finding large coverage holes when the
Publikováno v:
MLCAD
Coverage Directed Generation represents algorithms that are used to create tests or test-templates for hitting coverage events. Standard approaches for solving the problem use either user's intuition or random sampling. Recent work has been using opt
Publikováno v:
MLCAD
Advances in ML have revolutionized its effectiveness for a variety of applications. Indeed, in areas like image classification and NLP, ML (AI) has changed the rules of the game and opened the door to incredible advances. Design processes seem to mat
Autor:
Raviv Gal
Publikováno v:
Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD.