2019 International Conference On Computer Aided Design

The Premier Conference Devoted to Technical Innovations in Electronic Design Automation

November 4-7, 2019The Westin Westminster Westminster, CO

v class="event-details"> MP Associates, Inc.

TUESDAY November 06, 8:30am - 10:00am | Capri

Machine Learning for Electronic Design Automation: Modeling, Optimization, and Resilience
Pande Partha - Washington State Univ.
The rate of growth of Big Data, slowing down of Moore’s law, and the rise of emerging applications pose significant challenges in the design of large-scale computing systems with high-performance, energy-efficiency, and reliability. This special session will consider solutions based on machine learning and data analytics to address the following challenges: (1) How can we model the performance and power consumption of heterogeneous systems and interconnects using machine learning techniques? (2) How to use machine learning and statistical modeling for effective design space exploration of computing systems to optimize for power, performance, and thermal metrics? (3) How to use machine learning techniques to efficiently manage resources of computing systems (e.g., power, memory, interconnects) to improve performance and energy-efficiency? (4) How can data analytics facilitate fault diagnosis, detect anomalies, and increase robustness in the network backbone of emerging large-scale networking systems? To address these outstanding challenges, out-of-the-box approaches need to be explored. By integrating machine learning algorithms, data analytics, statistical modeling, and design of advanced computing systems, this session will engage a broad section of ICCAD conference attendees. This special session is targeted towards university researchers/professors, students, industry professionals, and computing system designers. This session will attract newcomers who want to learn how to apply machine learning and data analytics to solve problems in computing systems, as well as experienced researchers looking for exciting new directions in computing systems design, EDA methodologies, and multi-scale computing. This special session covers design, optimization and resilience: three main pillars of designing computing systems. It also highlights how machine learning and EDA researchers can join hands to design energy-efficient and reliable chips and systems.

4D.1Machine Learning for Performance and Power Modeling of Heterogeneous Systems
 Speaker: Joseph Greathouse - Advanced Micro Devices, Inc.
 Authors: Joseph Greathouse - Advanced Micro Devices, Inc.
Gabriel Loh - Advanced Micro Devices, Inc.
4D.2Machine Learning for Design Space Exploration and Optimization of Manycore Systems
 Speaker: Janardhan Rao Doppa - Washington State Univ.
 Authors: Ryan Gary Kim - Colorado State Univ.
Janardhan Rao Doppa - Washington State Univ.
Partha Pratim Pande - Washington State Univ.
4D.3Failure Prediction Based on Anomaly Detection for Complex Core Routers
 Speaker: Krishnendu Chakrabarty - Duke Univ.
 Authors: Shi Jin - Duke Univ.
Zhaobo Zhang - Huawei Technologies Co., Ltd.
Krishnendu Chakrabarty - Duke Univ.
Xinli Gu - Huawei Technologies Co., Ltd.