How to catch a lion in the desert: on the solution of the coverage directed generation (CDG) problem R Gal, E Haber, B Irwin, B Saleh, A Ziv Optimization and Engineering 22 (1), 217-245, 2021 | 14 | 2021 |
Using dnns and smart sampling for coverage closure acceleration R Gal, E Haber, A Ziv Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD, 15-20, 2020 | 10 | 2020 |
The Verification Cockpit – Creating the Dream Playground for Data Analytics over the Verification Process M Arar, M Behm, O Boni, R Gal, A Goldin, M Ilyaev, E Kermany, J Reysa, ... Hardware and Software: Verification and Testing: 11th International Haifa …, 2015 | 9 | 2015 |
Using deep neural networks and derivative free optimization to accelerate coverage closure R Gal, E Haber, B Irwin, M Mouallem, B Saleh, A Ziv 2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD (MLCAD), 1-6, 2021 | 7 | 2021 |
Automatic scalable system for the coverage-directed generation (cdg) problem R Gal, E Haber, W Ibraheem, B Irwin, Z Nevo, A Ziv 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 206-211, 2021 | 7 | 2021 |
Late breaking results: Friends-finding related interesting events via neighbor detection R Gal, H Kermany, A Ivrii, Z Nevo, A Ziv 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-2, 2020 | 6 | 2020 |
Template aware coverage: Taking coverage analysis to the next level R Gal, E Kermany, B Saleh, A Ziv, M Behm, B Hickerson Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 6 | 2017 |
ArChiVED: Architectural checking via event digests for high performance validation CH Hsu, D Chatterjee, R Morad, R Ga, V Bertacco 2014 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2014 | 5 | 2014 |
Diminution of test templates in test suites SS Ackerman, R Gal, A Koyfman, A Ziv US Patent 11,023,366, 2021 | 4 | 2021 |
Using machine learning clustering to find large coverage holes R Gal, G Simchoni, A Ziv Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD, 139-144, 2020 | 3 | 2020 |
Risk analysis based on design version control data R Gal, G Shurek, G Simchoni, A Ziv 2019 ACM/IEEE 1st Workshop on Machine Learning for CAD (MLCAD), 1-6, 2019 | 2 | 2019 |
Neural network accelerated implicit filtering: integrating neural network surrogates with provably convergent derivative free optimization methods B Irwin, E Haber, R Gal, A Ziv International Conference on Machine Learning, 14376-14389, 2023 | 1 | 2023 |
Coverage analysis with event clustering R Gal, A Ziv, G Simchoni US Patent 11,640,421, 2023 | 1 | 2023 |
Guest Editors’ Introduction: Special Issue on Machine Learning for CAD/EDA U Schlichtmann, B Li, B Yu, R Gal IEEE Design & Test 40 (1), 5-7, 2023 | 1 | 2023 |
Data Analytics and Machine Learning for Coverage Closure R Gal, W Ibraheem, Z Nevo, B Saleh, A Ziv Frontiers of Quality Electronic Design (QED) AI, IoT and Hardware Security …, 2022 | 1 | 2022 |
Machine Learning in the Service of Hardware Functional Verification R Gal, A Ziv Machine Learning Applications in Electronic Design Automation, 377-424, 2022 | 1 | 2022 |
Selecting test-templates using template-aware coverage data R Gal, G Simchoni, A Ziv US Patent 11,151,021, 2021 | 1 | 2021 |
Hardware verification based on relations between coverage events Z Nevo, A Ivrii, A Ziv, R Gal, H Kermany US Patent 10,984,159, 2021 | 1 | 2021 |
Hybrid checking for microarchitectural validation of microprocessor designs on acceleration platforms D Chatterjee, B Mammo, D Lee, R Gal, R Morad, A Nahir, A Ziv, ... 2013 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 311-317, 2013 | 1 | 2013 |
Generating data slices for machine learning validation O Raz, M Zalmanovici, ED Farchi, R Gal, A Ziv US Patent App. 17/109,259, 2022 | | 2022 |