16 research outputs found
AceleraciĂłn de algoritmos de procesamiento de imágenes para el análisis de partĂculas individuales con microscopia electrĂłnica
Tesis Doctoral inĂ©dita cotutelada por la Masaryk University (RepĂşblica Checa) y la Universidad AutĂłnoma de Madrid, Escuela PolitĂ©cnica Superior, Departamento de IngenierĂa Informática. Fecha de Lectura: 24-10-2022Cryogenic Electron Microscopy (Cryo-EM) is a vital field in current structural biology. Unlike X-ray
crystallography and Nuclear Magnetic Resonance, it can be used to analyze membrane proteins and
other samples with overlapping spectral peaks. However, one of the significant limitations of Cryo-EM
is the computational complexity. Modern electron microscopes can produce terabytes of data per single
session, from which hundreds of thousands of particles must be extracted and processed to obtain a
near-atomic resolution of the original sample. Many existing software solutions use high-Performance
Computing (HPC) techniques to bring these computations to the realm of practical usability. The
common approach to acceleration is parallelization of the processing, but in praxis, we face many
complications, such as problem decomposition, data distribution, load scheduling, balancing, and
synchronization. Utilization of various accelerators further complicates the situation, as heterogeneous
hardware brings additional caveats, for example, limited portability, under-utilization due to synchronization,
and sub-optimal code performance due to missing specialization.
This dissertation, structured as a compendium of articles, aims to improve the algorithms used
in Cryo-EM, esp. the SPA (Single Particle Analysis). We focus on the single-node performance
optimizations, using the techniques either available or developed in the HPC field, such as heterogeneous
computing or autotuning, which potentially needs the formulation of novel algorithms. The
secondary goal of the dissertation is to identify the limitations of state-of-the-art HPC techniques. Since
the Cryo-EM pipeline consists of multiple distinct steps targetting different types of data, there is no
single bottleneck to be solved. As such, the presented articles show a holistic approach to performance
optimization.
First, we give details on the GPU acceleration of the specific programs. The achieved speedup is
due to the higher performance of the GPU, adjustments of the original algorithm to it, and application
of the novel algorithms. More specifically, we provide implementation details of programs for movie
alignment, 2D classification, and 3D reconstruction that have been sped up by order of magnitude
compared to their original multi-CPU implementation or sufficiently the be used on-the-fly. In addition
to these three programs, multiple other programs from an actively used, open-source software package
XMIPP have been accelerated and improved.
Second, we discuss our contribution to HPC in the form of autotuning. Autotuning is the ability of
software to adapt to a changing environment, i.e., input or executing hardware. Towards that goal, we
present cuFFTAdvisor, a tool that proposes and, through autotuning, finds the best configuration of the
cuFFT library for given constraints of input size and plan settings. We also introduce a benchmark set
of ten autotunable kernels for important computational problems implemented in OpenCL or CUDA,
together with the introduction of complex dynamic autotuning to the KTT tool.
Third, we propose an image processing framework Umpalumpa, which combines a task-based
runtime system, data-centric architecture, and dynamic autotuning. The proposed framework allows for
writing complex workflows which automatically use available HW resources and adjust to different HW
and data but at the same time are easy to maintainThe project that gave rise to these results received the support of a fellowship from the “la Caixa”
Foundation (ID 100010434). The fellowship code is LCF/BQ/DI18/11660021.
This project has received funding from the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie grant agreement No. 71367
Proceedings, MSVSCC 2015
The Virginia Modeling, Analysis and Simulation Center (VMASC) of Old Dominion University hosted the 2015 Modeling, Simulation, & Visualization Student capstone Conference on April 16th. The Capstone Conference features students in Modeling and Simulation, undergraduates and graduate degree programs, and fields from many colleges and/or universities. Students present their research to an audience of fellow students, faculty, judges, and other distinguished guests. For the students, these presentations afford them the opportunity to impart their innovative research to members of the M&S community from academic, industry, and government backgrounds. Also participating in the conference are faculty and judges who have volunteered their time to impart direct support to their students’ research, facilitate the various conference tracks, serve as judges for each of the tracks, and provide overall assistance to this conference. 2015 marks the ninth year of the VMASC Capstone Conference for Modeling, Simulation and Visualization. This year our conference attracted a number of fine student written papers and presentations, resulting in a total of 51 research works that were presented. This year’s conference had record attendance thanks to the support from the various different departments at Old Dominion University, other local Universities, and the United States Military Academy, at West Point. We greatly appreciated all of the work and energy that has gone into this year’s conference, it truly was a highly collaborative effort that has resulted in a very successful symposium for the M&S community and all of those involved. Below you will find a brief summary of the best papers and best presentations with some simple statistics of the overall conference contribution. Followed by that is a table of contents that breaks down by conference track category with a copy of each included body of work. Thank you again for your time and your contribution as this conference is designed to continuously evolve and adapt to better suit the authors and M&S supporters.
Dr.Yuzhong Shen Graduate Program Director, MSVE Capstone Conference Chair
John ShullGraduate Student, MSVE Capstone Conference Student Chai
New computational methods toward atomic resolution in single particle cryo-electron microscopy
Tesis doctoral inĂ©dita leĂda en la Universidad AutĂłnoma de Madrid, Escuela PolitĂ©cnica Superior, Departamento de IngenierĂa Informática. Fecha de lectura: 22-06-2016Structural information of macromolecular complexes provides key insights into the way
they carry out their biological functions. In turn, Electron microscopy (EM) is an
essential tool to study the structure and function of biological macromolecules at a
medium-high resolution. In this context, Single-Particle Analysis (SPA), as an EM
modality, is able to yield Three-Dimensional (3-D) structural information for large biological
complexes at near atomic resolution by combining many thousands of projection
images. However, these views su er from low Signal-to-Noise Ratios (SNRs), since an
extremely low total electron dose is used during exposure to reduce radiation damage
and preserve the functional structure of macromolecules. In recent years, the emergence
of Direct Detection Devices (DDDs) has opened up the possibility of obtaining images
with higher SNRs. These detectors provide a set of frames instead of just one micrograph,
which makes it possible to study the behavior of frozen hydrated specimens as a
function of electron dose and rate. In this way, it has become apparent that biological
specimens embedded in a solid matrix of amorphous ice move during imaging, resulting
in Beam-Induced Motion (BIM). Therefore, alignment of frames should be added to the
classical standard data processing work
ow of single-particle reconstruction, which includes:
particle selection, particle alignment, particle classi cation, 3-D reconstruction,
and model re nement. In this thesis, we propose new algorithms and improvements for
three important steps of this work
ow: movie alignment, particles selection, and 3-D
reconstruction. For movie alignment, a methodology based on a robust to noise optical
ow approach is proposed that can e ciently correct for local movements and provide
quantitative analysis of the BIM pattern. We then introduce a method for automatic
particle selection in micrographs that uses some new image features to train two classi
ers to learn from the user the kind of particles he is interested in. Finally, for 3-D
reconstruction, we introduce a gridding-based direct Fourier method that uses a weighting
technique to compute a uniform sampled Fourier transform. The algorithms are
fully implemented in the open-source Xmipp package (http://xmipp.cnb.csic.es
Proceedings, MSVSCC 2013
Proceedings of the 7th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 11, 2013 at VMASC in Suffolk, Virginia
A Novel System and Image Processing for Improving 3D Ultrasound-guided Interventional Cancer Procedures
Image-guided medical interventions are diagnostic and therapeutic procedures that focus on minimizing surgical incisions for improving disease management and reducing patient burden relative to conventional techniques. Interventional approaches, such as biopsy, brachytherapy, and ablation procedures, have been used in the management of cancer for many anatomical regions, including the prostate and liver. Needles and needle-like tools are often used for achieving planned clinical outcomes, but the increased dependency on accurate targeting, guidance, and verification can limit the widespread adoption and clinical scope of these procedures. Image-guided interventions that incorporate 3D information intraoperatively have been shown to improve the accuracy and feasibility of these procedures, but clinical needs still exist for improving workflow and reducing physician variability with widely applicable cost-conscience approaches. The objective of this thesis was to incorporate 3D ultrasound (US) imaging and image processing methods during image-guided cancer interventions in the prostate and liver to provide accessible, fast, and accurate approaches for clinical improvements.
An automatic 2D-3D transrectal ultrasound (TRUS) registration algorithm was optimized and implemented in a 3D TRUS-guided system to provide continuous prostate motion corrections with sub-millimeter and sub-degree error in 36 ± 4 ms. An automatic and generalizable 3D TRUS prostate segmentation method was developed on a diverse clinical dataset of patient images from biopsy and brachytherapy procedures, resulting in errors at gold standard accuracy with a computation time of 0.62 s. After validation of mechanical and image reconstruction accuracy, a novel 3D US system for focal liver tumor therapy was developed to guide therapy applicators with 4.27 ± 2.47 mm error. The verification of applicators post-insertion motivated the development of a 3D US applicator segmentation approach, which was demonstrated to provide clinically feasible assessments in 0.246 ± 0.007 s. Lastly, a general needle and applicator tool segmentation algorithm was developed to provide accurate intraoperative and real-time insertion feedback for multiple anatomical locations during a variety of clinical interventional procedures. Clinical translation of these developed approaches has the potential to extend the overall patient quality of life and outcomes by improving detection rates and reducing local cancer recurrence in patients with prostate and liver cancer
Understanding Quantum Technologies 2022
Understanding Quantum Technologies 2022 is a creative-commons ebook that
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annealing and quantum simulation paradigms, history, science, research,
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around the world, quantum technologies societal impact and even quantum fake
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global view of how quantum technologies work, and particularly quantum
computing. This version is an extensive update to the 2021 edition published in
October 2021.Comment: 1132 pages, 920 figures, Letter forma
Generalized averaged Gaussian quadrature and applications
A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal