Brown University

Sherief Reda

Hokchhay Tann

Jacob Karl Rosenstein

Jason K Sello

Christopher Rose

Peter M Weber

Brenda Rubenstein

Amanda Doris Dombroski

Joseph D Geiser

Eamonn Kennedy

Eunsuk Kim

Christopher Arcadia

Kady M Oakley

Shui Ling Chen

Heng Zhao

Kapil Dev

Soheil Hashemi

R Iris Bahar

Abdullah Nowroz

The invention provides methods for computing with chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying chemical structure and/or concentration of at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at &#x3e;99% accuracy.

Methods of chemical computation

A hardware neural network system includes an input buffer for input neurons (Nbin), an output buffer for output neurons (Nbout), and a third buffer for synaptic weights (SB) connected to a Neural Functional Unit (NFU) and a control logic (CP) for performing synapses and neurons computations. The NFU pipelines a computation into stages, the stages including weight blocks (WB), an adder tree, and a non-linearity function.

Deep neural network

A method of accelerated iris recognition includes acquiring an image comprising at least an iris and a pupil, segmenting the iris and the pupil using a fully convolutional network (FCN) model, normalizing the segmented iris, encoding the normalized iris, the normalizing and encoding using a rubber sheet model and 1-D log Gabor filter, and masking the encoded iris.

Iris recognition using fully convolutional networks

This invention relates to a power mapping and modeling system for integrated circuits. An automated process includes determining a floor plan of the integrated circuit, dividing the integrated circuit into blocks based on the floor plan, pumping oil through an inlet valve, over the integrated circuit, and out an outlet valve to create a simulated oil-based cooling system, injecting a plurality of power pulses across the integrated circuit, applying infrared image techniques to the integrated circuit to create measured thermal images for the simulated oil-based cooling system, setting up a finite-element model (FEM) to estimate entries in a first thermal-to-power modeling matrix for the simulated oil-based cooling system, determining and storing performance monitoring counter (PMC) measurements related to power consumptions of the blocks of the integrated circuit, reconstructing a power dissipation for the simulated oil-based cooling system by using a thermal map for the simulated oil-based cooling system system, using the power dissipation of the simulated oil-based cooling system, the FEM, and the PMC measurements to create a thermal map for a copper based cooling system, and creating a final thermal-to-power model for the integrated circuit from the thermal map for the model copper based cooling system.

Power mapping and modeling system for integrated circuits

Growing community of inventors

Providence, RI, United States of America

Sherief Reda