Autonomic behavioural framework for structural parallelism over heterogeneous multi-core systems.

With the continuous advancement in hardware technologies, significant research has been devoted to design and develop high-level parallel programming models that allow programmers to exploit the latest developments in heterogeneous multi-core/many-core architectures. Structural programming paradigms propose a viable solution for e ciently programming modern heterogeneous multi-core architectures equipped with one or more programmable Graphics Processing Units (GPUs). Applying structured programming paradigms, it is possible to subdivide a system into building blocks (modules, skids or components) that can be independently created and then used in di erent systems to derive multiple functionalities. Exploiting such systematic divisions, it is possible to address extra-functional features such as application performance, portability and resource utilisations from the component level in heterogeneous multi-core architecture. While the computing function of a building block can vary for di erent applications, the behaviour (semantic) of the block remains intact. Therefore, by understanding the behaviour of building blocks and their structural compositions in parallel patterns, the process of constructing and coordinating a structured application can be automated. In this thesis we have proposed Structural Composition and Interaction Protocol (SKIP) as a systematic methodology to exploit the structural programming paradigm (Building block approach in this case) for constructing a structured application and extracting/injecting information from/to the structured application. Using SKIP methodology, we have designed and developed Performance Enhancement Infrastructure (PEI) as a SKIP compliant autonomic behavioural framework to automatically coordinate structured parallel applications based on the extracted extra-functional properties related to the parallel computation patterns. We have used 15 di erent PEI-based applications (from large scale applications with heavy input workload that take hours to execute to small-scale applications which take seconds to execute) to evaluate PEI in terms of overhead and performance improvements. The experiments have been carried out on 3 di erent Heterogeneous (CPU/GPU) multi-core architectures (including one cluster machine with 4 symmetric nodes with one GPU per node and 2 single machines with one GPU per machine). Our results demonstrate that with less than 3% overhead, we can achieve up to one order of magnitude speed-up when using PEI for enhancing application performance

DNA Tiles, Wang Tiles and Combinators

Abstract. In this paper we explore the relation betweenWang Tiles and Schonnkel Combinators in order to investigate Functional Combinators as an programming language for Self-assembly and DNA computing. We show: How any combinatorial program can be expressed in terms of Wang Tiles, and again, how any computation of the program ts into a grid of tiles of a suitable nite, tile set, and nally, how a program for Self-assembly DNA computing can be obtained. The result is a general methodology that, given any computable function, allows to dene a Self-assembly program that can be used to construct the computations of the functio

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum

Computation with photochromic memory

Unconventional computing is an area of research in which novel materials and paradigms are utilised to implement computation and data storage. This includes attempts to embed computation into biological systems, which could allow the observation and modification of living processes. This thesis explores the storage and computational capabilities of a biocompatible light-sensitive (photochromic) molecular switch (NitroBIPS) that has the potential to be embedded into both natural and synthetic biological systems. To achieve this, NitroBIPS was embedded in a (PDMS) polymer matrix and an optomechanical setup was built in order to expose the sample to optical stimulation and record fluorescent emission. NitroBIPS has two stable forms - one fluorescent and one non-fluorescent - and can be switched between the two via illumination with ultraviolet or visible light. By exposing NitroBIPS samples to specific stimulus pulse sequences and recording the intensity of fluorescence emission, data could be stored in registers and logic gates and circuits implemented. In addition, by moving the area of illumination, sub-regions of the sample could be addressed. This enabled parallel registers, Turing machine tapes and elementary cellular automata to be implemented. It has been demonstrated, therefore, that photochromic molecular memory can be used to implement conventional universal computation in an unconventional manner. Furthermore, because registers, Turing machine tapes, logic gates, logic circuits and elementary cellular automata all utilise the same samples and same hardware, it has been shown that photochromic computational devices can be dynamically repurposed. NitroBIPS and related molecules have been shown elsewhere to be capable of modifying many biological processes. This includes inhibiting protein binding, perturbing lipid membranes and binding to DNA in a manner that is dependent on the molecule's form. The implementation of universal computation demonstrated in this thesis could, therefore, be used in combination with these biological manipulations as key components within synthetic biology systems or in order to monitor and control natural biological processes