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Inter-disciplinary research challenges in computer systems for the 2020s


Albert Cohen, Xipeng Shen, Josep Torrellas, James Tuck, Yuanyuan Zhou, Sarita Adve, Ismail Akturk, Saurabh Bagchi, Rajeev Balasubramonian, Rajkishore Barik, Micah Beck, Ras Bodik, Ali Butt, Luis Ceze, Haibo Chen, Yiran Chen, Trishul Chilimbi, Mihai Christodorescu, John Criswell, Chen Ding, Yufei Ding, Sandhya Dwarkadas, Erik Elmroth, Phil Gibbons, Xiaochen Guo, Rajesh Gupta, Gernot Heiser, Hank Hoffman, Jian Huang, Hillery Hunter, John Kim, Sam King, James Larus, Chen Liu, Shan Lu, Brandon Lucia, Saeed Maleki, Somnath Mazumdar, Iulian Neamtiu, Keshav Pingali, Paolo Rech, Michael Scott, Yan Solihin, Dawn Song, Jakub Szefer, Dan Tsafrir, Bhuvan Urgaonkar, Marilyn Wolf, Yuan Xie, Jishen Zhao, Lin Zhong and Yuhao Zhu

National Science Foundation


The broad landscape of new technologies currently being explored makes the current times very exciting for computer systems research. The community is actively researching an extensive set of topics, ranging from the small (e.g., energy-independent embedded devices) to the large (e.g., brain-scale deep learning), simultaneously addressing technology discontinuities (End of Moore's Law and Energy Wall), new challenges in security and privacy, and the rise of artificial intelligence (AI).

While industry is applying some of these technologies, its efforts are necessarily focused on only a few areas, and on relatively short-term horizons. This offers academic researchers the opportunity to attack the problems with a broader and longer-term view. Further, in recent times, the computer systems community has started to pay increasing attention to non-performance measures, such as security, complexity, and power. To make progress in this multi-objective world, the composition of research teams needs to change. Teams have to become inter-disciplinary, enabling the flow of ideas across computing fields.

While many research directions are interesting, this report outlines a few high-priority areas where inter-disciplinary research is likely to have a high payoff:

  1. Developing the components for a usable planet-scale Internet of Things (IoT), with provably energy-efficient devices.2 This report envisions a highly-available, geographically distributed, heterogeneous large-scale IoT system with the same efficiency, maintainability, and usability as today's data centers. This planet-scale IoT will be populated by many computationally-sophisticated IoT devices that are ultra-low power and operate energy-independently.
  2. Rethinking the hardware-software security contract in the age of AI. In light of the recent security vulnerabilities, this report argues for building hardware abstractions that communicate security guarantees, and for allowing software to communicate its security and privacy requirements to the hardware. Further, security and privacy mechanisms should be integrated into the disruptive emerging technologies that support AI.
  3. Making AI a truly dependable technology that is usable by all the citizens in all settings. As AI frameworks automate an increasing number of critical operations, this report argues for end-to-end dependable AI, where both the hardware and the software are understood and verified. Further, AI needs to turn from a centralized tool into a capability easily usable by all the citizens in all settings to meet an ever expanding range of needs.
  4. Developing solutions to tackle extreme complexity, possibly based on formal methods. This report argues for the need to tame the explosion of system complexity and heterogeneity by creating new abstractions and complexity-management solutions. Such solutions need to be accessible to domain experts. An important step towards this goal is to scale out and extend formal methods for the real world.

This report also describes other, related research challenges.

BibTeX Entry

    author           = {Cohen, Albert and Shen, Xipeng and Torrellas, Josep and Tuck, James and Zhou, Yuanyuan and Adve,
                        Sarita and Akturk, Ismail and Bagchi, Saurabh and Balasubramonian, Rajeev and Barik, Rajkishore and
                        Beck, Micah and Bodik, Ras and Butt, Ali and Ceze, Luis and Chen, Haibo and Chen, Yiran and
                        Chilimbi, Trishul and Christodorescu, Mihai and Criswell, John and Ding, Chen and Ding, Yufei and
                        Dwarkadas, Sandhya and Elmroth, Erik and Gibbons, Phil and Guo, Xiaochen and Gupta, Rajesh and
                        Heiser, Gernot and Hoffman, Hank and Huang, Jian and Hunter, Hillery and Kim, John and King, Sam and
                        Larus, James and Liu, Chen and Lu, Shan and Lucia, Brandon and Maleki, Saeed and Mazumdar, Somnath
                        and Neamtiu, Iulian and Pingali, Keshav and Rech, Paolo and Scott, Michael and Solihin, Yan and
                        Song, Dawn and Szefer, Jakub and Tsafrir, Dan and Urgaonkar, Bhuvan and Wolf, Marilyn and Xie, Yuan
                        and Zhao, Jishen and Zhong, Lin and Zhu, Yuhao},
    title            = {Inter-Disciplinary Research Challenges in Computer Systems for the 2020s},
    month            = sep,
    year             = {2018},
    institution      = {National Science Foundation, USA}


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