Strategic Considerations for Neuromorphic Computing
This paper considers the interplay between algorithm and architecture advances and finds that cooperation can provide a much needed strategic advantage in the face of challenges for either spiking algorithms or spiking architectures to advance the field independently.
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 that 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. In this paper, we examine such research interactions through the lens of game theory. Our hope is that game theoretic analysis can provide greater insight into the decisions of neuromorphic co-design researchers and provide a formal argument that collaboration can be worth the cost. In particular, we consider the interplay between algorithm and architecture advances. The Colonel Blotto game is used to model and analyze different computing architectures, and the Stag Hunt model is used to analyze developments of spiking neural network algorithms and neuromorphic hardware as a co-design game. Our analysis illustrates challenges for either spiking algorithms or spiking architectures to advance the field independently. Instead, we find that cooperation can provide a much needed strategic advantage.