A reconfigurable, analog system for efficient stochastic biological computation

  • Marr B
  • Brink S
  • Hasler P
 et al. 
  • 11

    Readers

    Mendeley users who have this article in their library.
  • 1

    Citations

    Citations of this article.

Abstract

Motivated by the many stochastic processes found in biology that allow for ultra-efficient computing, this paper explores circuit implementations for stochastic computation in hardware. Several novel contributions are presented in this paper, namely a dynamically controllable system of random number generators that produces Bernoulli random variables, exponentially distributed random variables, and allows for random variables of an arbitrary distribution to be generated. This system is implemented on a reconfigurable analog chipset allowing for the first time ever a hardware stochastic process with a user input to control the probability distribution. The utility of this system is demonstrated by implementing the well-known Gillespie algorithm for simulating an arbitrary biological system trajectory of sufficiently small molecules where over a 127times performance improvement over current software approaches is shown.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free