Time: July 30 - August 2 (Mon-Thu)
Program: TTI-Chicago Summer Workshop Program
Main Outcomes: A closer collaboration between systems and theory researchers, bringing algorithms designers to work more closely with systems researchers, to understand the “gaps” and shortcomings with proposed solution approaches, with a focus on developing more collaborations to bridge such gaps. Expected benefits include - development of new problem domains, issues and constraints, and potentially usable solutions.
|6:00 p.m. - 8:00 p.m.||Evening reception|
|Monday - Thursday (maybe end by 5 on Thu)|
|9:00 a.m. - 10:00 a.m.||Plenary|
|10:00 a.m. - 10:30 a.m.||coffee break|
|10:30 a.m. - 12:30 p.m.||4 short talks|
|12:30 p.m. - 3:30 p.m.||Lunch break, working sessions (there will be lunch on Monday)|
|3:30 p.m. - 4:00 p.m.||Tea/coffee|
|4:00 p.m. - 5:30 p.m.||3 short talks|
|6:30 p.m.||Group dinner to be organized|
Modern data centers form the backbone on which all cloud services run. Most modern applications today are running on a data center. Data Centers themselves are incredibly complex with hundreds of thousands of machines, all connected by high speed networks, running thousands of applications, each running on hundreds of machines. Given the rapid pace of development, many of the central scheduling and resource management problems have been hurriedly solved, with quick and dirty solutions without careful evaluation of the efficacy of these methods. Algorithms to better manage the scale and complexity are critical to impacting scheduling and resource allocation policies, and in turn, the efficiency of the resource management policies drives both user happiness (e.g., response time) as well as running costs (e.g., energy usage), both critically important issues for the future. There are several questions that need to be addressed such as job scheduling across multiple clusters (or multiple data centers), sharing resources among competing applications, management of communication and I/O needs, and multi-resource aware job placement.
This workshop will bring together a team of researchers with complementary skills, both from theoretical computer science and systems with the ultimate goal of designing scheduling and resource allocation policies for the next generation of Data center Resource Management Systems (DRMS). While there is a huge scheduling literature in theory community, the success of translating the theoretical results to real systems have been limited. On one hand, a deeper understanding within the theory community of the real issues and constraints facing system builders and designers and building models for better modeling modern applications is required. On the other hand, system builders need to consider a more principled approach of tackling scheduling problems and using optimal, or close to optimal strategies that can significantly impact the design of heuristics used in resource management.
The workshop will give a unique opportunity to both the communities to spend a week together, identify the major issues, start collaboration and solve challenging technical questions. Data center scheduling is a complex problem, and many scheduling questions that we consider solved in theory needs to be revisited in light of it. Here we point out a few example questions that we propose to address during the workshop.