Accelerating pairwise sequence alignment on GPUs using the Wavefront Algorithm

Advances in genomics and sequencing technologies demand faster and more scalable analysis methods that can process longer sequences with higher accuracy. However, classical pairwise alignment methods, based on dynamic programming (DP), impose impractical computational requirements to align long and noisy sequences like those produced by PacBio, and Nanopore technologies. The recently proposed Wavefront Alignment (WFA) algorithm paves the way for more efficient alignment tools, improving time and memory complexity over previous methods. Notwithstanding the advantages of the WFA algorithm, modern high performance computing (HPC) platforms rely on accelerator-based architectures that exploit parallel computing resources to improve over classical computing CPUs. Hence, a GPU-enabled implementation of the WFA could exploit the hardware resources of modern GPUs and further accelerate sequence alignment in current genome analysis pipelines. This thesis presents two GPU-accelerated implementations based on the WFA for fast pairwise DNA sequence alignment: eWFA-GPU and WFA-GPU. Our first proposal, eWFA-GPU, computes the exact edit-distance alignment between two short sequences (up to a few thousand bases), taking full advantage of the massive parallel capabilities of modern GPUs. We propose a succinct representation of the alignment data that successfully reduces the overall amount of memory required, allowing the exploitation of the fast on-chip memory of a GPU. Our results show that eWFA-GPU outperforms by 3-9X the edit-distance WFA implementation running on a 20 core machine. Compared to other state-of-the-art tools computing the edit-distance, eWFA-GPU is up to 265X faster than CPU tools and up to 56 times faster than other GPU-enabled implementations. Our second contribution, the WFA-GPU tool, extends the work of eWFA-GPU to compute the exact gap-affine distance (i.e., a more general alignment problem) between arbitrary long sequences. In this work, we propose a CPU-GPU co-design capable of performing inter and intra-sequence parallel alignment of multiple sequences, combining a succinct WFA-data representation with an efficient GPU implementation. As a result, we demonstrate that our implementation outperforms the original WFA implementation between 1.5-7.7X times when computing the alignment path, and between 2.6-16X when computing only the alignment score. Moreover, compared to other state-of-the-art tools, the WFA-GPU is up to 26.7X faster than other GPU implementations and up to four orders of magnitude faster than other CPU implementations

FPGA Acceleration of Pre-Alignment Filters for Short Read Mapping With HLS

Pre-alignment filters are useful for reducing the computational requirements of genomic sequence mappers. Most of them are based on estimating or computing the edit distance between sequences and their candidate locations in a reference genome using a subset of the dynamic programming table used to compute Levenshtein distance. Some of their FPGA implementations of use classic HDL toolchains, thus limiting their portability. Currently, most FPGA accelerators offered by heterogeneous cloud providers support C/C++ HLS. In this work, we implement and optimize several state-of-the-art pre-alignment filters using C/C++ based-HLS to expand their portability to a wide range of systems supporting the OpenCL runtime. Moreover, we perform a complete analysis of the performance and accuracy of the filters and analyze the implications of the results. The maximum throughput obtained by an exact filter is 95.1 MPairs/s including memory transfers using 100 bp sequences, which is the highest ever reported for a comparable system and more than two times faster than previous HDL-based results. The best energy efficiency obtained from the accelerator (not considering host CPU) is 2.1 MPairs/J, more than one order of magnitude higher than other accelerator-based comparable approaches from the state of the art.10.13039/501100008530-European Union Regional Development Fund (ERDF) within the framework of the ERDF Operational Program of Catalonia 2014-2020 with a grant of 50% of the total cost eligible under the Designing RISC-V based Accelerators for next generation computers project (DRAC) (Grant Number: [001-P-001723]) 10.13039/501100002809-Catalan Government (Grant Number: 2017-SGR-313 and 2017-SGR-1624) 10.13039/501100004837-Spanish Ministry of Science, Innovation and Universities (Grant Number: PID2020-113614RB-C21 and RTI2018-095209-B-C22)Peer ReviewedPostprint (published version

Deployment of a HPC operational service

La cendra volcànica en suspensió crea greus problemes de seguretat i econòmics al sector aeronàutic. Les erupcions volcàniques que hi ha hagut fins ara han demostrat que és difícil aconseguir prediccions precises dels núvols de cendra. En aquest treball s'ha dissenyat i implementat un component per controlar processos HPC (en aquest cas, simulacions de dispersió de cendra volcànica), en un sistema operacional en temps real.Atmospheric dispersion of volcanic ash creates important economic and safety problems for the aviation industry. Past volcanic events have shown that is difficult to access precise forecasts of volcanic ash clouds. This project shows the design and implementation of a component for controlling remote HPC jobs (in this case, volcanic ash dispersion simulations), in a real-time operational system.La ceniza volcánica en suspensión crea graves problemas de seguridad y económicos en el sector aeronáutico. Las erupciones volcánicas que ha habido hasta ahora han demostrado que es difícil conseguir predicciones precisas de las nubes de ceniza. En este trabajo se ha diseñado e implementado un componente para controlar procesos HPC (en este caso, simulaciones de dispersión de ceniza volcánica), en un sistema operacional en tiempo real

Flocculation of Cellulose Microfiber and Nanofiber Induced by Chitosan–Xylan Complexes

This study aims to provide a comprehensive understanding of the key factors influencing the rheological behavior and the mechanisms of natural polyelectrolyte complexes (PECs) as flocculation agents for cellulose microfibers (CMFs) and nanofibers (CNFs). PECs were formed by combining two polyelectrolytes: xylan (Xyl) and chitosan (Ch), at different Xyl/Ch mass ratios: 60/40, 70/30, and 80/20. First, Xyl, Ch, and PEC solutions were characterized by measuring viscosity, critical concentration (c*), rheological parameter, ζ-potential, and hydrodynamic size. Then, the flocculation mechanisms of CMF and CNF suspensions with PECs under dynamic conditions were studied by measuring viscosity, while the flocculation under static conditions was examined through gel point measurements, floc average size determination, and ζ-potential analysis. The findings reveal that PEC solutions formed with a lower xylan mass ratio showed higher intrinsic viscosity, higher hydrodynamic size, higher z-potential, and a lower c*. This is due to the high molecular weight, charge, and gel-forming ability. All the analyzed solutions behave as a typical non-Newtonian shear-thinning fluid. The flocculation mechanisms under dynamic conditions showed that a very low dosage of PEC (between 2 and 6 mg PEC/g of fiber) was sufficient to produce flocculation. Under dynamic conditions, an increase in viscosity indicates flocculation at this low PEC dosage. Finally, under static conditions, maximum floc sizes were observed at the same PEC dosage where minimum gel points were reached. Higher PEC doses were required for CNF suspensions than for CMF suspensions.Fil: Bastida, Gabriela Adriana. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Tecnología Celulósica; ArgentinaFil: Tarrés, Quim. Universidad de Girona; EspañaFil: Aguado, Roberto. Universidad de Girona; EspañaFil: Delgado Aguilar, Marc. Universidad de Girona; EspañaFil: Zanuttini, Miguel Angel Mario. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Tecnología Celulósica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Galván, María Verónica. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Instituto de Tecnología Celulósica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentin

Accelerating edit-distance sequence alignment on GPU using the wavefront algorithm

Sequence alignment remains a fundamental problem with practical applications ranging from pattern recognition to computational biology. Traditional algorithms based on dynamic programming are hard to parallelize, require significant amounts of memory, and fail to scale for large inputs. This work presents eWFA-GPU, a GPU (graphics processing unit)-accelerated tool to compute the exact edit-distance sequence alignment based on the wavefront alignment algorithm (WFA). This approach exploits the similarities between the input sequences to accelerate the alignment process while requiring less memory than other algorithms. Our implementation takes full advantage of the massive parallel capabilities of modern GPUs to accelerate the alignment process. In addition, we propose a succinct representation of the alignment data that successfully reduces the overall amount of memory required, allowing the exploitation of the fast shared memory of a GPU. Our results show that our GPU implementation outperforms by 3- 9× the baseline edit-distance WFA implementation running on a 20 core machine. As a result, eWFA-GPU is up to 265 times faster than state-of-the-art CPU implementation, and up to 56 times faster than state-of-the-art GPU implementations.This work was supported in part by the European Unions’s Horizon 2020 Framework Program through the DeepHealth Project under Grant 825111; in part by the European Union Regional Development Fund within the Framework of the European Regional Development Fund (ERDF) Operational Program of Catalonia 2014–2020 with a Grant of 50% of Total Cost Eligible through the Designing RISC-V-based Accelerators for next-generation Computers Project under Grant 001-P-001723; in part by the Ministerio de Ciencia e Innovacion (MCIN) Agencia Estatal de Investigación (AEI)/10.13039/501100011033 under Contract PID2020-113614RB-C21 and Contract TIN2015-65316-P; and in part by the Generalitat de Catalunya (GenCat)-Departament de Recerca i Universitats (DIUiE) (GRR) under Contract 2017-SGR-313, Contract 2017-SGR-1328, and Contract 2017-SGR-1414. The work of Miquel Moreto was supported in part by the Spanish Ministry of Economy, Industry and Competitiveness under Ramon y Cajal Fellowship under Grant RYC-2016-21104.Peer ReviewedPostprint (published version

OpenCL-based FPGA accelerator for semi-global approximate string matching using diagonal bit-vectors

An FPGA accelerator for the computation of the semi-global Levenshtein distance between a pattern and a reference text is presented. The accelerator provides an important benefit to reduce the execution time of read-mappers used in short-read genomic sequencing. Previous attempts to solve the same problem in FPGA use the Myers algorithm following a column approach to compute the dynamic programming table. We use an approach based on diagonals that allows for some resource savings while maintaining a very high throughput of 1 alignment per clock cycle. The design is implemented in OpenCL and tested on two FPGA accelerators. The maximum performance obtained is 91.5 MPairs/s for 100 × 120 sequences and 47 MPairs/s for 300 × 360 sequences, the highest ever reported for this problem.This research was supported by the EU Regional Development Fund under the DRAC project [001-P-001723], by the MINECO-Spain (contract TIN2017-84553-C2-1-R), by the MICIU-Spain (contract RTI2018-095209-B-C22) and by the Catalan government (contracts 2017-SGR-1624, 2017-SGR313, 2017-SGR-1328). M.M. was partially supported by the MINECO under RYC-2016-21104. We thank Intel for granting us access to the DevCloud system and let us join the HARP research program. The presented HARP-2 results were obtained on resources hosted at the Paderborn Center for Parallel Computing (PC2) in the Intel Hardware Accelerator Research Program (HARP2).Peer ReviewedPostprint (author's final draft

Micro- and Nanofibrillated Cellulose from Annual Plant-Sourced Fibers: Comparison between Enzymatic Hydrolysis and Mechanical Refining

The current trends in micro-/nanofibers offer a new and unmissable chance for the recovery of cellulose from non-woody crops. This work assesses a technically feasible approach for the production of micro- and nanofibrillated cellulose (MNFC) from jute, sisal and hemp, involving refining and enzymatic hydrolysis as pretreatments. Regarding the latter, only slight enhancements of nanofibrillation, transparency and specific surface area were recorded when increasing the dose of endoglucanases from 80 to 240 mg/kg. This supports the idea that highly ordered cellulose structures near the fiber wall are resistant to hydrolysis and hinder the diffusion of glucanases. Mechanical MNFC displayed the highest aspect ratio, up to 228 for hemp. Increasing the number of homogenization cycles increased the apparent viscosity in most cases, up to 0.14 Pa·s at 100 s−1 (1 wt.% consistency). A shear-thinning behavior, more marked for MNFC from jute and sisal, was evidenced in all cases. We conclude that, since both the raw material and the pretreatment play a major role, the unique characteristics of non-woody MNFC, either mechanical or enzymatically pretreated (low dose), make it worth considering for large-scale processes

Electrospray Deposition of Cellulose Nanofibers on Paper: Overcoming the Limitations of Conventional Coating

While the potential of cellulose nanofibers to enhance the mechanical and barrier properties of paper is well-known, there are many uncertainties with respect to how to apply them. In this study, we use not only bulk addition of micro-/nanofibers and bar coating with oxidized nanofibers, but also a combination of these and, as a novel element, electrospray deposition of nanofiber dispersions. Characterization involved testing the strength of uncoated and coated paper sheets, their resistance to air flow, their Bendtsen roughness, and their apparent density, plus visualization of their surface and cross-sections by scanning electron microscopy. As expected, bulk addition to the unrefined pulp was sufficient to attain substantial strengthening, but this enhancement was limited to approximately 124%. Following this, surface addition by bar coating improved air resistance, but not strength, since, as applying nanocellulose at high consistency was technically unfeasible, this was performed several times with detrimental drying stages in between. However, replacing bar coating with electrospraying helped us overcome these apparent limitations, producing enhancements in both barrier and tensile properties. It is concluded that electrosprayed nanofibers, owing to their uniform deposition and favorable interactions, operate as an effective binder between fibers (and/or fines)

Valorization of Kraft Lignin from Black Liquor in the Production of Composite Materials with Poly(caprolactone) and Natural Stone Groundwood Fibers

The development of new materials is currently focused on replacing fossil-based plastics with sustainable materials. Obtaining new bioplastics that are biodegradable and of the greenest possible origin could be a great alternative for the future. However, there are some limitations—such as price, physical properties, and mechanical properties—of these bioplastics. In this sense, the present work aims to explore the potential of lignin present in black liquor from paper pulp production as the main component of a new plastic matrix. For this purpose, we have studied the simple recovery of this lignin using acid precipitation, its thermoplastification with glycerin as a plasticizing agent, the production of blends with poly(caprolactone) (PCL), and finally the development of biocomposite materials reinforcing the blend of thermoplastic lignin and PCL with stone groundwood fibers (SGW). The results obtained show that thermoplastic lignin alone cannot be used as a bioplastic. However, its combination with PCL provided a tensile strength of, e.g., 5.24 MPa in the case of a 50 wt.% blend. In addition, when studying the properties of the composite materials, it was found that the tensile strength of a blend with 20 wt.% PCL increased from 1.7 to 11.2 MPa with 40 wt.% SGW. Finally, it was proven that through these biocomposites it is possible to obtain a correct fiber–blend interface

High-Yield Pulp from Brassica napus to Manufacture Packaging Paper

The stalks that are left on the field after harvesting rapeseed crops could be used to make packaging grade paper. This work evaluates the suitability of mechanical and thermomechanical pulps from rapeseed stalks for papermaking, with a view to alleviating the limitations of recycled fluting. Their performance was compared to that of commercial fluting (recycled fluting) of the same basis weight, 100 g/m2, and to that of virgin pulps from pine wood. The thermomechanical pulp was refined to improve key mechanical properties. Its drainability was found to be very low, even before refining, and its breaking length after beating to 1200 PFI revolutions, 4 km, surpassed that of sheets of recycled fluting that were obtained under similar conditions. These findings support the hypothesis that high-yield pulps from rapeseed stalks are a strong choice of virgin fibres to produce fluting and, generally speaking, packaging paper.ECOWAL Group, Molelular Biology and Biochemical Engineering Dpt. Universidad Pablo de Olavide, Road of Utrera Km.1, 41013 Seville, Spain