HSP-Wrap: The Design and Evaluation of Reusable Parallelism for a Subclass of Data-Intensive Applications

There is an increasing gap between the rate at which data is generated by scientific and non-scientific fields and the rate at which data can be processed by available computing resources. In this paper, we introduce the fields of Bioinformatics and Cheminformatics; two fields where big data has become a problem due to continuing advances in the technologies that drives these fields: such as gene sequencing and small ligand exploration. We introduce high performance computing as a means to process this growing base of data in order to facilitate knowledge discovery. We enumerate goals of the project including reusability, efficiency, reliability, and scalability. We then describe the implementation of a software scheduler which aims to improve input and output performance of a targeted collection of informatics tools, as well as the profiling and optimization needed to tune the software. We evaluate the performance of the software with a scalability study of the Bioinformatics tools BLAST, HMMER, and MUSCLE; as well as the Cheminformatics tool DOCK6

High integrity hardware-software codesign

Programmable logic devices (PLDs) are increasing in complexity and speed, and are being used as important components in safety-critical systems. Methods for developing high-integrity software for these systems are well-known, but this is not true for programmable logic. We propose a process for developing a system incorporating software and PLDs, suitable for safety critical systems of the highest levels of integrity. This process incorporates the use of Synchronous Receptive Process Theory as a semantic basis for specifying and proving properties of programs executing on PLDs, and extends the use of SPARK Ada from a programming language for safety-critical systems software to cover the interface between software and programmable logic. We have validated this approach through the specification and development of a substantial safety-critical system incorporating both software and programmable logic components, and the development of tools to support this work. This enables us to claim that the methods demonstrated are not only feasible but also scale up to realistic system sizes, allowing development of such safety-critical software-hardware systems to the levels required by current system safety standards

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Sub-nanosecond Cherenkov photon detection for LHCb particle identification in high-occupancy conditions and semiconductor tracking for muon scattering tomography

The increase in luminosity during the LHC upgrade programme causes a challenging rise in track multiplicity and hit occupancy in the LHCb detector. In order to mitigate this effect, the use of photon detector hit time information is presented in the context of the Ring-Imaging Cherenkov (RICH) detectors. The application of a time gate in the FPGA of the digital readout board for the Upgrade Ia photon detector, which is being installed for LHC Run 3, is described. Data recorded during SPS charged particle beam tests using a 6.25 ns time gate show a reduction of up to a factor of four in asynchronous detector noise compared to the original 25ns readout. A time-walk correction based on the time-over- threshold is proposed. Using the LHCb simulation framework, the intrinsic time resolution of the RICH detectors is demonstrated to be less than 10 ps. This is particularly relevant for the LHCb Upgrade II, which is scheduled for the year 2030 in preparation for a further order- of-magnitude rise in luminosity. Methods of time gating and scaling of the signal amplitude in the RICH reconstruction likelihood maximisation algorithm are presented. The results show that, considering improvements in the time-resolution only, a photon detector with an approximately 50 ps resolution can achieve today’s particle ID performance in the high- luminosity LHC environment. In the second part of this thesis, the first published semiconductor tracker for cosmic-ray muon scattering tomography is presented. The tracker uses silicon strip sensors from the ATLAS Semiconductor Tracker (SCT) with an 80μm pitch. A novel electronic readout system for the sensors is designed, based on a scalable, inexpensive, flexible, FPGA-based solution. A high-precision mechanical structure with integrated cooling is built to align the SCT modules. This alignment is fine-tuned in software, and the tracker performance is compared with a Geant4 simulation. A scattering angle resolution compatible with 1.5 mrad at the 4 GeV average cosmic-ray muon energy is obtained. Data are recorded for plastic, iron and lead samples using 45000 muons. Images are reconstructed using the Angle Statistics Reconstruction algorithm, and demonstrate good contrast between low and high atomic number materials