Neuromorphic Co-Design as a Game (2312.14954v1)
Abstract: Co-design is a prominent topic presently in computing, speaking to the mutual benefit of coordinating design choices of several layers in the technology stack. For example, this may be designing algorithms which can most efficiently take advantage of the acceleration properties of a given architecture, while simultaneously designing the hardware to support the structural needs of a class of computation. The implications of these design decisions are influential enough to be deemed a lottery, enabling an idea to win out over others irrespective of the individual merits. Coordination is a well studied topic in the mathematics of game theory, where in many cases without a coordination mechanism the outcome is sub-optimal. Here we consider what insights game theoretic analysis can offer for computer architecture co-design. In particular, we consider the interplay between algorithm and architecture advances in the field of neuromorphic computing. Analyzing developments of spiking neural network algorithms and neuromorphic hardware as a co-design game we use the Stag Hunt model to illustrate challenges for spiking algorithms or architectures to advance the field independently and advocate for a strategic pursuit to advance neuromorphic computing.
- A new golden age for computer architecture. Communications of the ACM, 62(2):48–60, 2019.
- David A Patterson Hennessy. Computer architecture: A quantitative approach by john l. Hennessy, David A. Patterson, 2017.
- Sara Hooker. The hardware lottery. Communications of the ACM, 64(12):58–65, 2021.
- Opportunities for neuromorphic computing algorithms and applications. Nature Computational Science, 2(1):10–19, 2022.
- A review of non-cognitive applications for neuromorphic computing. Neuromorphic Computing and Engineering, 2022.
- James B Aimone. Neural algorithms and computing beyond moore’s law. Communications of the ACM, 62(4):110–110, 2019.
- Steve Furber. Large-scale neuromorphic computing systems. Journal of neural engineering, 13(5):051001, 2016.
- Spiking neural networks hardware implementations and challenges: A survey. ACM Journal on Emerging Technologies in Computing Systems (JETC), 15(2):1–35, 2019.
- A survey of neuromorphic computing and neural networks in hardware. arXiv preprint arXiv:1705.06963, 2017.
- 2022 roadmap on neuromorphic computing and engineering. Neuromorphic Computing and Engineering, 2(2):022501, 2022.
- Theory of games and economic behavior, 2nd rev. 1947.
- A course in game theory. MIT press, 1994.
- Game theory, alive, volume 101. American Mathematical Soc., 2017.
- Prajit K Dutta. Strategies and games: theory and practice. MIT press, 1999.
- Tim Roughgarden. Algorithmic game theory. Communications of the ACM, 53(7):78–86, 2010.
- Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge university press, 2010.
- A single ‘weight-lifting’game covers all kinds of games. Royal Society Open Science, 6(11):191602, 2019.
- A general theory of equilibrium selection in games. MIT Press Books, 1, 1988.
- Advancing neuromorphic computing with loihi: A survey of results and outlook. Proceedings of the IEEE, 109(5):911–934, 2021.
- Mike Davies. New tools for a new era of neuromorphic computing, Mar 2022. URL https://flagship.kip.uni-heidelberg.de/jss/HBPm?m=displayPresentation&mI=235&mEID=8950.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.