Hector Fabio Restrepo

CryptoBooster: A Reconfigurable and Modular Cryptographic Coprocessor

The CryptoBooster is a modular and reconfigurable cryptographic coprocessor that takes full advantage of current high-performance reconfigurable circuits (FPGAs) and their partial reconfigurability. The CryptoBooster works as a coprocessor with a host system in order to accelerate cryptographic operations. A series of cryptographic modules for different encryption algorithms are planned. The first module we implemented is IDEACore, an encryption core for the International Data Encryption Algorithm (IDEA?).

A networked FPGA-based hardware implementation of a neural network application

Describes a networked FPGA-based implementation of the FAST (Flexible Adaptable-Size Topology) architecture, an artificial neural network (ANN) that dynamically adapts its size. Most ANN models base their ability to adapt to problems on changing the strength of the interconnections between computational elements according to a given learning algorithm. However, constrained interconnection structures may limit such ability. Field programmable hardware devices are very well adapted for the implementation of ANNs with in-circuit structure adaptation. To realize this implementation, we used a network of Labomat-3 boards (a reconfigurable platform developed in our laboratory), which communicate with each other using TCP/IP or a faster direct hardware connection.

An Embryonics Implementation of a Self-Replicating Universal Turing Machine

This paper describes a multicellular universal Turing machine implementation endowed with self-replication and self-repair capabilities. In this multicellular artificial organism every artificial cell contains a complete copy of the genome. The mapping of the universal Turing machine onto a multicellular array was made possible thanks to the introduction of a modified version of the W-machine1.

Implementation of a self-replicating universal Turing machine

The goal of this contribution is to describe how a universal Turing machine was embedded into a hardware system in order to verify the computational universality of a novel architecture. This implementation was realized with a multicellular automaton inspired by the embryonic development of living organisms. In such an architecture, every artificial “cell” contains a complete copy of the description of the machine, a redundancy that allows the introduction of the properties of self-repair and self-replication. These properties were coupled with a modified version of the W-machine to realize a robust, self-replicating universal computer in actual hardware.

A 2-by-n Hybrid Cellular Automaton Implementation Using a Bio-Inspired FPGA

This paper presents the detailed implementation of a 2-by-n hybrid cellular automaton by using the MICTREE (for tree of micro-instructions) cell, a new kind of coarse-grained field-programmable gate array (FPGA) developed in the framework of the Embryonics project. This cell will be used for the implementation of multicellular artificial organisms with biological-like properties, i.e., capable of self-repair and self-replication.

A reconfigurable platform for academic purposes

Labomat 3 is a reconfigurable platform for teaching and research purposes developed by our laboratory. The main features of the board are: (1) a microprocessor associated with two mid-range FPGAs, (2) a powerful multitasking real-time operating system including a JavaVM, (3) easy to use design tools, and (4) a networking interface. In this paper we describe the hardware and software of the board as well as some application domains.