Automated wordlength optimization framework for multi-source statistical interval-based analysis of nonlinear systems with control-flow structures

El uso de aritmética de punto fijo es una opción de diseño muy extendida en sistemas con fuertes restricciones de área, consumo o rendimiento. Para producir implementaciones donde los costes se minimicen sin impactar negativamente en la precisión de los resultados debemos llevar a cabo una asignación cuidadosa de anchuras de palabra. Encontrar la combinación óptima de anchuras de palabra en coma fija para un sistema dado es un problema combinatorio NP-hard al que los diseñadores dedican entre el 25 y el 50 % del ciclo de diseño. Las plataformas hardware reconfigurables, como son las FPGAs, también se benefician de las ventajas que ofrece la aritmética de coma fija, ya que éstas compensan las frecuencias de reloj más bajas y el uso más ineficiente del hardware que hacen estas plataformas respecto a los ASICs. A medida que las FPGAs se popularizan para su uso en computación científica los diseños aumentan de tamaño y complejidad hasta llegar al punto en que no pueden ser manejados eficientemente por las técnicas actuales de modelado de señal y ruido de cuantificación y de optimización de anchura de palabra. En esta Tesis Doctoral exploramos distintos aspectos del problema de la cuantificación y presentamos nuevas metodologías para cada uno de ellos: Las técnicas basadas en extensiones de intervalos han permitido obtener modelos de propagación de señal y ruido de cuantificación muy precisos en sistemas con operaciones no lineales. Nosotros llevamos esta aproximación un paso más allá introduciendo elementos de Multi-Element Generalized Polynomial Chaos (ME-gPC) y combinándolos con una técnica moderna basada en Modified Affine Arithmetic (MAA) estadístico para así modelar sistemas que contienen estructuras de control de flujo. Nuestra metodología genera los distintos caminos de ejecución automáticamente, determina las regiones del dominio de entrada que ejercitarán cada uno de ellos y extrae los momentos estadísticos del sistema a partir de dichas soluciones parciales. Utilizamos esta técnica para estimar tanto el rango dinámico como el ruido de redondeo en sistemas con las ya mencionadas estructuras de control de flujo y mostramos la precisión de nuestra aproximación, que en determinados casos de uso con operadores no lineales llega a tener tan solo una desviación del 0.04% con respecto a los valores de referencia obtenidos mediante simulación. Un inconveniente conocido de las técnicas basadas en extensiones de intervalos es la explosión combinacional de términos a medida que el tamaño de los sistemas a estudiar crece, lo cual conlleva problemas de escalabilidad. Para afrontar este problema presen tamos una técnica de inyección de ruidos agrupados que hace grupos con las señales del sistema, introduce las fuentes de ruido para cada uno de los grupos por separado y finalmente combina los resultados de cada uno de ellos. De esta forma, el número de fuentes de ruido queda controlado en cada momento y, debido a ello, la explosión combinatoria se minimiza. También presentamos un algoritmo de particionado multi-vía destinado a minimizar la desviación de los resultados a causa de la pérdida de correlación entre términos de ruido con el objetivo de mantener los resultados tan precisos como sea posible. La presente Tesis Doctoral también aborda el desarrollo de metodologías de optimización de anchura de palabra basadas en simulaciones de Monte-Cario que se ejecuten en tiempos razonables. Para ello presentamos dos nuevas técnicas que exploran la reducción del tiempo de ejecución desde distintos ángulos: En primer lugar, el método interpolativo aplica un interpolador sencillo pero preciso para estimar la sensibilidad de cada señal, y que es usado después durante la etapa de optimización. En segundo lugar, el método incremental gira en torno al hecho de que, aunque es estrictamente necesario mantener un intervalo de confianza dado para los resultados finales de nuestra búsqueda, podemos emplear niveles de confianza más relajados, lo cual deriva en un menor número de pruebas por simulación, en las etapas iniciales de la búsqueda, cuando todavía estamos lejos de las soluciones optimizadas. Mediante estas dos aproximaciones demostramos que podemos acelerar el tiempo de ejecución de los algoritmos clásicos de búsqueda voraz en factores de hasta x240 para problemas de tamaño pequeño/mediano. Finalmente, este libro presenta HOPLITE, una infraestructura de cuantificación automatizada, flexible y modular que incluye la implementación de las técnicas anteriores y se proporciona de forma pública. Su objetivo es ofrecer a desabolladores e investigadores un entorno común para prototipar y verificar nuevas metodologías de cuantificación de forma sencilla. Describimos el flujo de trabajo, justificamos las decisiones de diseño tomadas, explicamos su API pública y hacemos una demostración paso a paso de su funcionamiento. Además mostramos, a través de un ejemplo sencillo, la forma en que conectar nuevas extensiones a la herramienta con las interfaces ya existentes para poder así expandir y mejorar las capacidades de HOPLITE. ABSTRACT Using fixed-point arithmetic is one of the most common design choices for systems where area, power or throughput are heavily constrained. In order to produce implementations where the cost is minimized without negatively impacting the accuracy of the results, a careful assignment of word-lengths is required. The problem of finding the optimal combination of fixed-point word-lengths for a given system is a combinatorial NP-hard problem to which developers devote between 25 and 50% of the design-cycle time. Reconfigurable hardware platforms such as FPGAs also benefit of the advantages of fixed-point arithmetic, as it compensates for the slower clock frequencies and less efficient area utilization of the hardware platform with respect to ASICs. As FPGAs become commonly used for scientific computation, designs constantly grow larger and more complex, up to the point where they cannot be handled efficiently by current signal and quantization noise modelling and word-length optimization methodologies. In this Ph.D. Thesis we explore different aspects of the quantization problem and we present new methodologies for each of them: The techniques based on extensions of intervals have allowed to obtain accurate models of the signal and quantization noise propagation in systems with non-linear operations. We take this approach a step further by introducing elements of MultiElement Generalized Polynomial Chaos (ME-gPC) and combining them with an stateof- the-art Statistical Modified Affine Arithmetic (MAA) based methodology in order to model systems that contain control-flow structures. Our methodology produces the different execution paths automatically, determines the regions of the input domain that will exercise them, and extracts the system statistical moments from the partial results. We use this technique to estimate both the dynamic range and the round-off noise in systems with the aforementioned control-flow structures. We show the good accuracy of our approach, which in some case studies with non-linear operators shows a 0.04 % deviation respect to the simulation-based reference values. A known drawback of the techniques based on extensions of intervals is the combinatorial explosion of terms as the size of the targeted systems grows, which leads to scalability problems. To address this issue we present a clustered noise injection technique that groups the signals in the system, introduces the noise terms in each group independently and then combines the results at the end. In this way, the number of noise sources in the system at a given time is controlled and, because of this, the combinato rial explosion is minimized. We also present a multi-way partitioning algorithm aimed at minimizing the deviation of the results due to the loss of correlation between noise terms, in order to keep the results as accurate as possible. This Ph.D. Thesis also covers the development of methodologies for word-length optimization based on Monte-Carlo simulations in reasonable times. We do so by presenting two novel techniques that explore the reduction of the execution times approaching the problem in two different ways: First, the interpolative method applies a simple but precise interpolator to estimate the sensitivity of each signal, which is later used to guide the optimization effort. Second, the incremental method revolves on the fact that, although we strictly need to guarantee a certain confidence level in the simulations for the final results of the optimization process, we can do it with more relaxed levels, which in turn implies using a considerably smaller amount of samples, in the initial stages of the process, when we are still far from the optimized solution. Through these two approaches we demonstrate that the execution time of classical greedy techniques can be accelerated by factors of up to ×240 for small/medium sized problems. Finally, this book introduces HOPLITE, an automated, flexible and modular framework for quantization that includes the implementation of the previous techniques and is provided for public access. The aim is to offer a common ground for developers and researches for prototyping and verifying new techniques for system modelling and word-length optimization easily. We describe its work flow, justifying the taken design decisions, explain its public API and we do a step-by-step demonstration of its execution. We also show, through an example, the way new extensions to the flow should be connected to the existing interfaces in order to expand and improve the capabilities of HOPLITE.

Mechanism-based inhibition of the melatonin rhythm enzyme: Pharmacologic exploitation of active site functional plasticity

Serotonin N-acetyltransferase is the enzyme responsible for the diurnal rhythm of melatonin production in the pineal gland of animals and humans. Inhibitors of this enzyme active in cell culture have not been reported previously. The compound N-bromoacetyltryptamine was shown to be a potent inhibitor of this enzyme in vitro and in a pineal cell culture assay (IC50 ≈ 500 nM). The mechanism of inhibition is suggested to involve a serotonin N-acetyltransferase-catalyzed alkylation reaction between N-bromoacetyltryptamine and reduced CoA, resulting in the production of a tight-binding bisubstrate analog inhibitor. This alkyltransferase activity is apparently catalyzed at a functionally distinct site compared with the acetyltransferase activity active site on serotonin N-acetyltransferase. Such active site plasticity is suggested to result from a subtle conformational alteration in the protein. This plasticity allows for an unusual form of mechanism-based inhibition with multiple turnovers, resulting in “molecular fratricide.” N-bromoacetyltryptamine should serve as a useful tool for dissecting the role of melatonin in circadian rhythm as well as a potential lead compound for therapeutic use in mood and sleep disorders.

Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

Crystal structures of bovine milk xanthine dehydrogenase and xanthine oxidase: Structure-based mechanism of conversion

Mammalian xanthine oxidoreductases, which catalyze the last two steps in the formation of urate, are synthesized as the dehydrogenase form xanthine dehydrogenase (XDH) but can be readily converted to the oxidase form xanthine oxidase (XO) by oxidation of sulfhydryl residues or by proteolysis. Here, we present the crystal structure of the dimeric (Mr, 290,000) bovine milk XDH at 2.1-Å resolution and XO at 2.5-Å resolution and describe the major changes that occur on the proteolytic transformation of XDH to the XO form. Each molecule is composed of an N-terminal 20-kDa domain containing two iron sulfur centers, a central 40-kDa flavin adenine dinucleotide domain, and a C-terminal 85-kDa molybdopterin-binding domain with the four redox centers aligned in an almost linear fashion. Cleavage of surface-exposed loops of XDH causes major structural rearrangement of another loop close to the flavin ring (Gln 423—Lys 433). This movement partially blocks access of the NAD substrate to the flavin adenine dinucleotide cofactor and changes the electrostatic environment of the active site, reflecting the switch of substrate specificity observed for the two forms of this enzyme.

An alternative pathway to β-carotene formation in plant chromoplasts discovered by map-based cloning of Beta and old-gold color mutations in tomato

Carotenoid pigments in plants fulfill indispensable functions in photosynthesis. Carotenoids that accumulate as secondary metabolites in chromoplasts provide distinct coloration to flowers and fruits. In this work we investigated the genetic mechanisms that regulate accumulation of carotenoids as secondary metabolites during ripening of tomato fruits. We analyzed two mutations that affect fruit pigmentation in tomato (Lycopersicon esculentum): Beta (B), a single dominant gene that increases β-carotene in the fruit, and old-gold (og), a recessive mutation that abolishes β-carotene and increases lycopene. Using a map-based cloning approach we cloned the genes B and og. Molecular analysis revealed that B encodes a novel type of lycopene β-cyclase, an enzyme that converts lycopene to β-carotene. The amino acid sequence of B is similar to capsanthin-capsorubin synthase, an enzyme that produces red xanthophylls in fruits of pepper (Capsicum annum). Our results prove that β-carotene is synthesized de novo during tomato fruit development by the B lycopene cyclase. In wild-type tomatoes B is expressed at low levels during the breaker stage of ripening, whereas in the Beta mutant its transcription is dramatically increased. Null mutations in the gene B are responsible for the phenotype in og, indicating that og is an allele of B. These results confirm that developmentally regulated transcription is the major mechanism that governs lycopene accumulation in ripening fruits. The cloned B genes can be used in various genetic manipulations toward altering pigmentation and enhancing nutritional value of plant foods.

Structure-based assignment of the biochemical function of a hypothetical protein: A test case of structural genomics

Many small bacterial, archaebacterial, and eukaryotic genomes have been sequenced, and the larger eukaryotic genomes are predicted to be completely sequenced within the next decade. In all genomes sequenced to date, a large portion of these organisms’ predicted protein coding regions encode polypeptides of unknown biochemical, biophysical, and/or cellular functions. Three-dimensional structures of these proteins may suggest biochemical or biophysical functions. Here we report the crystal structure of one such protein, MJ0577, from a hyperthermophile, Methanococcus jannaschii, at 1.7-Å resolution. The structure contains a bound ATP, suggesting MJ0577 is an ATPase or an ATP-mediated molecular switch, which we confirm by biochemical experiments. Furthermore, the structure reveals different ATP binding motifs that are shared among many homologous hypothetical proteins in this family. This result indicates that structure-based assignment of molecular function is a viable approach for the large-scale biochemical assignment of proteins and for discovering new motifs, a basic premise of structural genomics.

Computer-based analysis of the binding steps in protein complex formation

Computer models were used to examine whether and under what conditions the multimeric protein complex is inhibited by high concentrations of one of its components—an effect analogous to the prozone phenomenon in precipitin tests. A series of idealized simple “ball-and-stick” structures representing small oligomeric complexes of protein molecules formed by reversible binding reactions were analyzed to determine the binding steps leading to each structure. The equilibrium state of each system was then determined over a range of starting concentrations and Kds and the steady-state concentration of structurally complete oligomer calculated for each situation. A strong inhibitory effect at high concentrations was shown by any protein molecule forming a bridge between two or more separable parts of the complex. By contrast, proteins linked to the outside of the complex by a single bond showed no inhibition whatsoever at any concentration. Nonbridging, multivalent proteins in the body of the complex could show an inhibitory effect or not depending on the structure of the complex and the strength of its bonds. On the basis of this study, we suggest that the prozone phenomenon will occur widely in living cells and that it could be a crucial factor in the regulation of protein complex formation.

Population based study of risk factors for underdiagnosis of asthma in adolescence: Odense schoolchild study

Objective: To describe factors related to underdiagnosis of asthma in adolescence.