Artificial life programming in the robust-first attractor

Despite mounting awareness of the liabilities of deterministic CPU and RAM computing, across industry and academia there remains little clear vision of a fundamental, generalpurpose alternative. To obtain indefinitely scalable computer architectures offering improved robustness and security, we have advocated a realignment of the roles of hardware and software based on artificial life principles. In this paper we propose an active media computational abstraction to underlie such a hardware-software renegotiation. The active media framework is much in the spirit of probabilistic cellular automata, but designed for indefinite scalability and serious programmability, rather than simplicity and analytic tractability. We discuss active media programming techniques based on living systems principles, and present anecdotal data from sample programs to introduce a new programming language called ulam, that we are developing as an underlying language for active media.

[1]  David H. Ackley,et al.  Indefinitely Scalable Computing = Artificial Life Engineering , 2014, ALIFE.

[2]  S. Wolfram.  Statistical mechanics of cellular automata , 1983 .

[3]  Rodney A. Brooks,et al.  Asynchrony induces stability in cellular automata based models , 1994 .

[4]  Grinstein,et al.  Statistical mechanics of probabilistic cellular automata. , 1985, Physical review letters.

[5]  Richard M. Karp,et al.  An introduction to randomized algorithms , 1991, Discret. Appl. Math..

[6]  Shekhar Y. Borkar,et al.  iWarp: an integrated solution to high-speed parallel computing , 1988, Proceedings. SUPERCOMPUTING '88.

[7]  Erik D. Demaine,et al.  Reconfigurable asynchronous logic automata: (RALA) , 2010, POPL '10.

[8]  Darko Stefanovic,et al.  A deoxyribozyme-based molecular automaton , 2003, Nature Biotechnology.

[9]  Hans-J. Boehm.  Position paper: nondeterminism is unavoidable, but data races are pure evil , 2012, RACES '12.

[10]  David H. Ackley,et al.  A Movable Architecture for Robust Spatial Computing , 2013, Comput. J..

[11]  Tommaso Toffoli,et al.  Cellular automata machines - a new environment for modeling , 1987, MIT Press series in scientific computation.

[12]  Dmitri B. Strukov,et al.  Race Logic: A hardware acceleration for dynamic programming algorithms , 2014, 2014 ACM/IEEE 41st International Symposium on Computer Architecture (ISCA).

[13]  Sandeep K. Shukla,et al.  Guest Editors' Introduction: GALS Design and Validation , 2007, IEEE Design & Test of Computers.

[14]  David H. Ackley.  Beyond efficiency , 2013, Commun. ACM.

[15]  David H. Ackley,et al.  Pursue Robust Indefinite Scalability , 2011, HotOS.

[16]  Gernot Heiser,et al.  The von Neumann Architecture Is Due for Retirement , 2013, HotOS.

[17]  David H. Ackley.  Bespoke Physics for Living Technology , 2013, Artificial Life.

[18]  Andrew S. Cassidy,et al.  A million spiking-neuron integrated circuit with a scalable communication network and interface , 2014, Science.

[19]  Alexandru Agapie,et al.  Probabilistic Cellular Automata , 2014, J. Comput. Biol..

[20]  Martin C. Rinard,et al.  Parallelizing Sequential Programs with Statistical Accuracy Tests , 2013, TECS.

[21]  Thomas S. Ray.  A Proposal to Create a Network-Wide Biodiversity Reserve For Digital Organisms , 1995 .

[22]  Randall D. Beer,et al.  The Cognitive Domain of a Glider in the Game of Life , 2014, Artificial Life.

[23]  Vijayalakshmi Srinivasan,et al.  Programming with relaxed synchronization , 2012, RACES '12.

[24]  Franck Cappello,et al.  Toward Exascale Resilience , 2009, Int. J. High Perform. Comput. Appl..

[25]  D. Endy,et al.  Refinement and standardization of synthetic biological parts and devices , 2008, Nature Biotechnology.