2,250 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Guided rewriting and constraint satisfaction for parallel GPU code generation
Graphics Processing Units (GPUs) are notoriously hard to optimise for manually due to their scheduling and memory hierarchies. What is needed are good automatic code generators and optimisers for such parallel hardware. Functional approaches such as Accelerate, Futhark and LIFT leverage a high-level algorithmic Intermediate Representation (IR) to expose parallelism and abstract the implementation details away from the user. However, producing efficient code for a given accelerator remains challenging. Existing code generators depend on the user input to choose a subset of hard-coded optimizations or automated exploration of implementation search space. The former suffers from the lack of extensibility, while the latter is too costly due to the size of the search space. A hybrid approach is needed, where a space of valid implementations is built automatically and explored with the aid of human expertise.
This thesis presents a solution combining user-guided rewriting and automatically generated constraints to produce high-performance code. The first contribution is an automatic tuning technique to find a balance between performance and memory consumption. Leveraging its functional patterns, the LIFT compiler is empowered to infer tuning constraints and limit the search to valid tuning combinations only.
Next, the thesis reframes parallelisation as a constraint satisfaction problem. Parallelisation constraints are extracted automatically from the input expression, and a solver is used to identify valid rewriting. The constraints truncate the search space to valid parallel mappings only by capturing the scheduling restrictions of the GPU in the context of a given program. A synchronisation barrier insertion technique is proposed to prevent data races and improve the efficiency of the generated parallel mappings.
The final contribution of this thesis is the guided rewriting method, where the user encodes a design space of structural transformations using high-level IR nodes called rewrite points. These strongly typed pragmas express macro rewrites and expose design choices as explorable parameters. The thesis proposes a small set of reusable rewrite points to achieve tiling, cache locality, data reuse and memory optimisation.
A comparison with the vendor-provided handwritten kernel ARM Compute Library and the TVM code generator demonstrates the effectiveness of this thesis' contributions. With convolution as a use case, LIFT-generated direct and GEMM-based convolution implementations are shown to perform on par with the state-of-the-art solutions on a mobile GPU. Overall, this thesis demonstrates that a functional IR yields well to user-guided and automatic rewriting for high-performance code generation
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well
Modular Collaborative Program Analysis
With our world increasingly relying on computers, it is important to ensure the quality, correctness, security, and performance of software systems. Static analysis that computes properties of computer programs without executing them has been an important method to achieve this for decades. However, static analysis faces major chal-
lenges in increasingly complex programming languages and software systems and increasing and sometimes conflicting demands for soundness, precision, and scalability. In order to cope with these challenges, it is necessary to build static analyses for complex problems from small, independent, yet collaborating modules that can be developed in isolation and combined in a plug-and-play manner.
So far, no generic architecture to implement and combine a broad range of dissimilar static analyses exists. The goal of this thesis is thus to design such an architecture and implement it as a generic framework for developing modular, collaborative static analyses. We use several, diverse case-study analyses from which we systematically derive requirements to guide the design of the framework. Based on this, we propose the use of a blackboard-architecture style collaboration of analyses that we implement in the OPAL framework. We also develop a formal model of our architectures core concepts and show how it enables freely composing analyses while retaining their soundness guarantees.
We showcase and evaluate our architecture using the case-study analyses, each of which shows how important and complex problems of static analysis can be addressed using a modular, collaborative implementation style. In particular, we show how a modular architecture for the construction of call graphs ensures consistent soundness of different algorithms. We show how modular analyses for different aspects of immutability mutually benefit each other. Finally, we show how the analysis of method purity can benefit from the use of other complex analyses in a collaborative manner and from exchanging different analysis implementations that exhibit different characteristics. Each of these case studies improves over the respective state of the art in terms of soundness, precision, and/or scalability and shows how our architecture enables experimenting with and fine-tuning trade-offs between these qualities
Decryption Failure Attacks on Post-Quantum Cryptography
This dissertation discusses mainly new cryptanalytical results related to issues of securely implementing the next generation of asymmetric cryptography, or Public-Key Cryptography (PKC).PKC, as it has been deployed until today, depends heavily on the integer factorization and the discrete logarithm problems.Unfortunately, it has been well-known since the mid-90s, that these mathematical problems can be solved due to Peter Shor's algorithm for quantum computers, which achieves the answers in polynomial time.The recently accelerated pace of R&D towards quantum computers, eventually of sufficient size and power to threaten cryptography, has led the crypto research community towards a major shift of focus.A project towards standardization of Post-quantum Cryptography (PQC) was launched by the US-based standardization organization, NIST. PQC is the name given to algorithms designed for running on classical hardware/software whilst being resistant to attacks from quantum computers.PQC is well suited for replacing the current asymmetric schemes.A primary motivation for the project is to guide publicly available research toward the singular goal of finding weaknesses in the proposed next generation of PKC.For public key encryption (PKE) or digital signature (DS) schemes to be considered secure they must be shown to rely heavily on well-known mathematical problems with theoretical proofs of security under established models, such as indistinguishability under chosen ciphertext attack (IND-CCA).Also, they must withstand serious attack attempts by well-renowned cryptographers both concerning theoretical security and the actual software/hardware instantiations.It is well-known that security models, such as IND-CCA, are not designed to capture the intricacies of inner-state leakages.Such leakages are named side-channels, which is currently a major topic of interest in the NIST PQC project.This dissertation focuses on two things, in general:1) how does the low but non-zero probability of decryption failures affect the cryptanalysis of these new PQC candidates?And 2) how might side-channel vulnerabilities inadvertently be introduced when going from theory to the practice of software/hardware implementations?Of main concern are PQC algorithms based on lattice theory and coding theory.The primary contributions are the discovery of novel decryption failure side-channel attacks, improvements on existing attacks, an alternative implementation to a part of a PQC scheme, and some more theoretical cryptanalytical results
General Course Catalog [2022/23 academic year]
General Course Catalog, 2022/23 academic yearhttps://repository.stcloudstate.edu/undergencat/1134/thumbnail.jp
Gamma-Ray Spectroscopy of Neutron-Deficient Nuclides 129Nd, 131Pm and 132Pm
The newly commissioned MARA recoil separator has been coupled with the efficient high-purity germanium (HPGe) JUROGAM γ-ray spectrometer and a suite of focal-plane detector systems to facilitate detailed studies of in-beam and isomeric delayed radiation emitted by various types of nuclides. Excited quantum states were populated in the highly neutron-deficient nuclides 129Nd, 131Pm and 132Pm utilising the fusion-evaporation reaction 58Ni + 78Kr > 136 Gd∗.
In the study of 129Nd, three new isomeric states were observed at excitation energies of 1893, 2109 and 2284 keV, respectively. The state at 2284 keV was measured to have a half-life of 679 ± 60 ns. Excited states existing above this level were measured using the JUROGAM spectrometer and characterised within the framework of the cranked shell model.
The study of 131Pm focused on detailed in-beam γ-ray measurements, resulting in extensions to the yrast band at high and low spin. To accommodate the lowest spin states, reinterpretation of the band in terms of its deformation aligned nature resulted in reassignment of the yrast band to Nilsson orbital [532]5/2−. The lowest spin state of 5/2− is then proposed to be the ground state, in agreement with theoretical studies.
Finally, band extensions at high and low spin were made in the study of doubly odd 132Pm. Two low-spin isomeric states were measured, with half-lives of 187 ± 4 ns and 19.9 ± 0.5 μs. γ radiation observed to depopulate these states is proposed to feed the ground state of the this nucleus, allowing unambiguous assignment of absolute excitation energies for two of the four observed bands
Micropipette Manipulation for the Production and Characterisation of Microparticles in Biomaterials Discovery
The use of microparticles for biological applications is increasing, and with it, the need for specialised microparticles. While one of the major advantages of microparticles is the ability to fine-tune properties, such as chemistry and morphology to best serve an application, achieving this usually relies on lengthy trial-and-error processes.
Micropipette manipulation techniques have proven to be valuable tools in studying cell mechanics, protein dehydration and material characterisation. The techniques permit the study of simple and complex multicomponent systems from an alternative perspective to traditional techniques. Utilising these techniques droplets and particle forming systems can be studied on the microscale and in real time. Thus, providing improved understanding of microparticle formation and aiding in particle design and optimisation. The hypothesis for this work was that micropipette manipulation techniques can be employed to understand and improve formation of bio-instructive microparticles.
In this thesis, micropipette manipulation techniques were used to study a series of microparticle systems. To better enable this application, methods were developed to improve or extend existing analysis practices. The new routines allowed for a reduction in measurement error to the limit of detection, improved efficiency, and increased processing capabilities. Additionally new methods were developed for analysing droplet microstructure.
A comprehensive assessment of the impact of the most widely utilised microparticle materials, poly(vinyl alcohol) (PVA) and poly(D, L lactic acid) (PDLLA), on solvent/water interfaces was conducted using the static equilibrium interfacial tension method. The polymers were treated as additives to two solvent/water combination base systems (dichloromethane (DCM) and ethyl acetate.) From this assessment empirical equations were derived for calculating the interfacial tension for given concentrations of the polymers. The maximum interfacial tension for DCM/water to remain as stable drops during particle formation was determined as approximately 11.1 mN m-1. Droplet dissolution was assessed for both base solvents with a range of PDLLA/PVA concentrations. The diffusion coefficients for the base solvents in water were 17 ± 3.8 x10-6 cm2 s-1 (DCM) and 10.1 ± 0.28 x10-6 cm2 s-1 (ethyl acetate). Negligible change was seen for the addition of polymer to either phase. Comparisons to the Epstein-Plesset model and the activity-based model for dissolution were conducted for both solvents for the range of PDLLA concentrations concerned. Dissolution followed the curve of the Epstein-Plesset model but deviated from the expected final size given by the activity-based dissolution model.
A series of novel, bio-instructive surfactants were assessed for their use in particle formation through the polymerisation of monomer droplets produced using droplet microfluidics. The effectiveness of the different surfactants was determined using static equilibrium interfacial tension measurements. Different core monomers, polymer architecture and hydrophilic and hydrophobic components were considered. Optimum concentrations of surfactants were taken into droplet microfluidics for optimised particle production. Flow maps were generated mathematically using the optimised compositions and showed good agreement with the stable regions found experimentally. Investigations of material transfer between the monomer drop and the surroundings showed unusual behaviour by the monomer for which a mechanism is proposed to explain such behaviour.
A dual surfactant system for enabling the production of biodegradable microparticles using droplet microfluidics was investigated and the concentrations optimised for performance and application criteria. The particles produced using PDLLA in ethyl acetate formed secondary droplets both inside and on the surface of drop as dissolution occurred. By varying the concentrations of surfactant, core polymer and continuous phase saturation, the morphology of these particles could be manipulated. Using EGPEA-mPEGMA it was possible to generate a topography, reproducible between single particles studies and high volume microparticle production, that could be controlled by adjusting surfactant concentration.
The studies presented here demonstrate the improved understanding of selected microparticle formation systems through the application of micropipette manipulation techniques. Characterisation of novel biomaterials was conducted which in turn allowed the optimisation of bio-instructive microparticles through droplet microfluidics
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