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Registers-Optimized neuro-Chip Knowledge Emulation Technology (ROCKET™) is a software simulator of a neural chip based on RBF (Radial
Basis Function) architecture and RCE (Restricted Coulomb Energy) learning
algorithm. Unlike a software "emulator" which can simply reproduce
the functionality at the API level, the software "simulator"
reproduces all the registers of the chip and performs bitwise operations on
the registers in an extremely efficient way. The simulator was written in C
language using all the potentialities that the language offers (inside our
safety critical subset) to speed up execution on Von Neumann machines. The
simulation uses a proprietary algorithm that speeds up the
"broadcasting" operation on a Von Neumann machine. This simulator
cannot parallelize operations on vector prototypes as the chip does: the
hardware chip is based on a scalable SIMD (Single Instruction Multiple Data)
architecture. This simulator can be considered the most efficient software
implementation of an RBF-like neural network
architecture with RCE learning algorithm (classifier). The ROCKET™ simulator
has been updated to be compliant with all the evolutions of the chip from
ZISC36® to ZISC78® to NM500® and ANM5500®.
In the software simulation the number of neurons is unlimited for all
the versions. This neuro-Chip software simulation
has been successfully applied in the biomedical sector within an ECG
recognizer and in robotics within an anomaly detector for prognostic
maintenance. |
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©2024_Luca_Marchese_All_Rights_Reserved Aerospace_&_Defence_Machine_Learning_Company VAT:_IT0267070992 NATO_CAGE_CODE:_AK845 Email:_luca.marchese@synaptics.org |
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