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Abstract: Most of cryptographic systems are based on modular exponentiation, wherein the operands are considerably large. Generally, modular exponentiation is implemented using a chain of modular multiplications. One way of improving the throughput of a cryptographic system implementation is reducing the number of the required modular multiplications. Given the exponent, finding the minimal number of multiplications that are necessary to reach the exponentiation results is a hard problem. We take advantage of an evolutionary stochastic process, commonly called genetic algorithms, to compute minimal addition chains, allow us to reduce drastically the number of the required modular multiplications. In this paper, we investigate two different ways to implement modular exponentiation based on the evolved addition chain: the first approach consists of implementing all the exponentiation operation on hardware and the second approach combines software and hardware. While the first approach attempts to optimise the encryption/decryption throughput regardless of the cost of system implementation, the second attempts to reach a balance between the throughput and the cost of the implementation. [Copyright &y& Elsevier]

Abstract: DNA sequence matching is used in the identification of a relationship between a fragment of DNA and its owner by mean of a database of DNA registers. A DNA fragment could be a hair sample left at a crime scene by a suspect or provided by a person for a paternity exam. The process of aligning and matching DNA sequences is a computationally demanding process. In this paper, we propose a novel parallel hardware architecture for DNA matching based on the steps of the BLAST algorithm. The design is scalable so that its structure can be adjusted depending on the size of the subject and query DNA sequences. Moreover, the number of units used to perform in parallel can also be scaled depending some characteristics of the algorithm. The design was synthesized and programmed into FPGA. The trade-off between cost and performance were analyzed to evaluate different design configuration. [Copyright &y& Elsevier]

Abstract: Radioactivity is the spontaneous emission of energy from unstable atoms. Radioactive sources have radionuclides. Radionuclide undergoes radioactive decay and emits gamma rays and subatomic particles, constituting the ionizing radiation. The gamma ray energy of a radionuclide is used to determine the identity of gamma emitters present in the source. This paper describes the hardware implementation of subtractive clustering algorithm to perform radionuclide identification. The hardware was proven to be effective for this task, allowing scalability to increase parallelism in the computations. [Copyright &y& Elsevier]