Optimal Scheduling and Allocation for IC Design Management and Cost Reduction

Author:

Agrawal Prabhav1,Broxterman Mike2,Chatterjee Biswadeep3,Cuevas Patrick2,Hayashi Kathy H.2,Kahng Andrew B.1,Myana Pranay K.1,Nath Siddhartha1

Affiliation:

1. UC San Diego, La Jolla, CA

2. Qualcomm, Inc., Morehouse Drive, San Diego, CA

3. Qualcomm India Private Limited, Whitefield, Bangalore KA

Abstract

A large semiconductor product company spends hundreds of millions of dollars each year on design infrastructure to meet tapeout schedules for multiple concurrent projects. Resources (servers, electronic design automation tool licenses, engineers, and so on) are limited and must be shared -- and the cost per day of schedule slip can be enormous. Co-constraints between resource types (e.g., one license per every two cores (threads)) and dedicated versus shareable resource pools make scheduling and allocation hard. In this article, we formulate two mixed integer-linear programs for optimal multi-project, multi-resource allocation with task precedence and resource co-constraints. Application to a real-world three-project scheduling problem extracted from a leading-edge design center of anonymized Company X shows substantial compute and license costs savings. Compared to the product company, our solution shows that the makespan of schedule of all projects can be reduced by seven days, which not only saves ∼ 2.7% of annual labor and infrastructure costs but also enhances market competitiveness. We also demonstrate the capability of scheduling over two dozen chip development projects at the design center level, subject to resource and datacenter capacity limits as well as per-project penalty functions for schedule slips. The design center ended up purchasing 600 additional servers, whereas our solution demonstrates that the schedule can be met without having to purchase any additional servers. Application to a four-project scheduling problem extracted from a leading-edge design center in a non-US location shows availability of up to ∼ 37% headcount reduction during a half-year schedule for just one type of chip design activity.

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications

Reference48 articles.

1. P. Agrawal B. Chatterjee A. B. Kahng P. K. Myana and S. Nath. 2015. Optimal multi-tapeout project scheduling for enterprise-scale design management and cost reduction. Work-in-Progress DAC. P. Agrawal B. Chatterjee A. B. Kahng P. K. Myana and S. Nath. 2015. Optimal multi-tapeout project scheduling for enterprise-scale design management and cost reduction. Work-in-Progress DAC.

2. M. Ayala and C. Artigues. 2010. On Integer Linear Programming Formulations for the Resource-Constrained Modulo Scheduling Problem Rapport LAAS. Technical Report 10393. M. Ayala and C. Artigues. 2010. On Integer Linear Programming Formulations for the Resource-Constrained Modulo Scheduling Problem Rapport LAAS. Technical Report 10393.

3. Tight LP bounds for resource constrained project scheduling

4. D. Bienstock and M. Zuckerberg. 2009. A new LP algorithm for precedence constrained production scheduling. Optimization Online 1--33. D. Bienstock and M. Zuckerberg. 2009. A new LP algorithm for precedence constrained production scheduling. Optimization Online 1--33.

5. CROSS cyclic resource-constrained scheduling solver

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