Characterizing and Accelerating Bioinformatics Workloads on Modern Microarchitectures

Bioinformatics, the use of computer techniques to analyze biological data, has been a particularly active research field in the last two decades. Advances in this field have contributed to the collection of enormous amounts of data, and the sheer amount of available data has started to overtake the processing capability possible with current computer systems. Clearly, computer architects need to have a better understanding of how bioinformatics applications work and what kind of architectural techniques could be used to accelerate these important scientific workloads on future processors. In this dissertation, we develop a bioinformatic benchmark suite and provide a detailed characterization of these applications in common use today from a computer architect's point of view. We analyze a wide range of detailed execution characteristics including instruction mix, IPC measurements, L1 and L2 cache misses on a real architecture; and proceed to analyze the workloads' memory access characteristics. We then concentrate on accelerating a particularly computationally intensive bioinformatics workload on the novel Cell Broadband Engine multiprocessor architecture. The HMMER workload is used for protein profile searching using hidden Markov models, and most of its execution time is spent running the Viterbi algorithm. We parallelize and partition the HMMER application to implement it on the Cell Broadband Engine. In order to run the Viterbi algorithm on the 256KB local stores of the Cell BE synergistic processing units (SPEs), we present a method to develop a fast SIMD implementation of the Viterbi algorithm that reduces the storage requirements significantly. Our HMMER implementation for the Cell BE architecture, Cell-HMMER, exploits the multiple levels of parallelism inherent in this application, and can run protein profile searches up to 27.98 times faster than a modern dual-core x86 microprocessor

Computación de alto desempeño aplicada en técnicas de simulación de proteínas

Se busca estudiar alternativas de computación de alto desempeño (HPC) viables en la PUJ para generar opciones que permitan potenciar la e-Science y el trabajo interdisciplinario. Para ello se revisó el estado del arte y la necesidad de HPC, observando posibles problemas que demuestren las ventajas de tener un sistema con estas características, se diseñó un experimento de simulación utilizando clusters computacionales diferenciados según capacidad y cantidad de procesadores| se seleccionaron las moléculas según resultados experimentales, se seleccionaron variables independientes, dependientes e intervinientes para preparar y configurar las simulaciones. Se desarrollaron scripts y programas para replicar configuraciones en las máquinas.Magíster en Ciencias BiológicasMaestrí

Estudio molecular de pacientes colombianos afectados por enanismo esencial

Los síndromes de enanismo esencial microcefálico son un grupo de enfermedades monogénicas infrecuentes que se caracterizan principalmente por talla baja extrema proporcionada de inicio prenatal y microcefalia severa. En los pacientes que formaron parte del presente estudio se investigaron variantes en el gen PCNT debido a que presentaban hallazgos clínicos compatibles con el síndrome MOPD II (enanismo esencial osteodisplásico microcefálico tipo II). Posteriormente, se amplió el estudio con una secuenciación de exoma en una paciente con variantes heterocigotas en el gen PCNT que no explicaban el fenotipo, encontrando una variante nueva en el gen DDX11 y realizando el diagnóstico de Síndrome de Warsaw Breakage en esta paciente.Microcephalic primordial dwarfism syndromes are a group of rare monogenic diseases that are characterized primarily by extreme low stature of prenatal onset and severe microcephaly. In patients who participated in the study, variants in the gene PCNT was investigated because they had clinical findings consistent with the MOPD II (Microcephalic osteodisplastic primordial dwarfism type II) syndrome. The study was expanded with exome sequencing in a patient who presented heterozygous variants in the PCNT gene, which could not explain the phenotype. This find gave room for the discovery of a new variant in the DDX11 gene that allowed for the diagnosis of the Warsaw Breakage syndrome in the patient

Workload Characterization of Bioinformatics Applications

The exponential growth in the amount of genomic information has spurred growing interest in large scale analysis of genetic data. Bioinformatics applications represent the increasingly important workloads. However, very few results on the behavior of these applications running on the state-of-the-art microprocessor and systems have been published. This paper proposes a suite of widely used bioinformatics applications and studies the execution characteristics of these benchmarks on a representative architecture – the Intel Pentium 4. To understand the impacts and implications of bioinformatics workloads on the microprocessor designs, we contrast the characteristics of bioinformatics workloads and the widely used SPEC 2000 integer benchmarks. The proposed bioinformatics benchmark suite as well as the input datasets can be downloaded from the following website