Optical Turing Machine (OTM)
Objectives: Optical computing and transmission using the same encoding format.
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Today:
Electronics goes faster by increasing parallelism; optics by increasing
density (bits per symbol). The difference complicates in-network
processing, which requires serial-parallel and binary-symbol translation,
which are costly, complex, and inefficient. Current optical computing
seeks to emulate switched, binary electronics, still requiring translation.
Approach:
OTM develops multibit symbol logic using encodings with continuous
transforms, enabled by recent advances in nonlinear optical processing.
This supports computation and transmission using a single format,
avoiding translation. It avoids the switching, binary limitations and
transform discontinuities that make optical processing difficult.
Interest:
Supports Tbps processing of optically-encoded data, e.g., for in-network
forwarding, security, data mining, and filtering (deep inspection). Useful
for optical networking, big data and data centers, VPNs, and firewalls.
Impact:
In-network processing avoiding both OEO and optical format
translation, resulting in simpler devices, lower power, and higher speed.
Risks:
Signal regeneration is critical and remains challenging. The design space
is large and could require advances in many disciplines.
Support:
Seeking to develop a proof-of-concept prototype. Contact us for our
specific goals.
Targets:
Components needed for typical in-network functions: symbol logic for
common in-network functions, encoding for continuous transforms,
symbol comparator, bistable latch for control, basic signal regeneration.
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For more information please visit http://www.isi.edu/otm
or contact Joe Touch [email protected]
USC Information Sciences Institute • 4676 Admiralty Way • Marina del Rey, CA 90202