Enzyme contribution of non-Saccharomyces yeasts to wine production

The fermentation of grape must to produce wine is a biologically complex process, carried on by yeasts and malolactic bacteria. The yeasts present in spontaneous fermentation may be divided into two groups, the Saccharomyces yeasts, particularly S. cerevisiae, and the non-Saccharomyces yeasts which include members of the genera Rhodotorula, Pichia, Candida, Debaryomyces, Metschtnikowia, Hansenula and Hanseniaspora. S. cerevisiae yeasts are able to convert sugar into ethanol and CO2 via fermentation. They have been used for thousands of years by mankind for the production of fermented beverages and foods, including wine. Their enzymes provide interesting wine organoleptic characteristics. β-Glucosidase activity is involved in the release of terpenes to wine, thus contributing to varietal aroma. β-Xylosidase enzyme is also interesting in industry due to its involvement in the degradation of hemicellulose by hydrolyzing its main heteroglycan (xylan). The ability of yeasts to release proteases has been observed by many researchers because of their potential to degrade haze proteins in wine and to generate nutrient sources for microorganisms. Moreover, these enzymes are interesting in biotechnology, for use in food processing such as cheese, pickles or sausage

Saiph, a domain specific language for computational fluid dynamics simulations

Nowadays, High-Performance Computing (HPC) is assuming an increasingly central role in scientific research while computer architectures are becoming more and more hetero-geneous and using different parallel programming models and techniques. Under this scenario, the only way to successfully exploit an HPC system requires that computer and domain scientists work closely towards producing applications to solve domain problems, ensuring productivity and performance at the same time. Facing such purpose, Saiph is a Domain Specific Language designed to ease the task of solving couple and uncouple Partial Differential Equations (PDE’s), with a primary focusing on Computational Fluid Dynamics (CFD) applications. Saiph allows to model complex physical phenomena featured by PDE’s, easing the use of numerical methods and optimizations on different computer architectures to the users

Extending OmpSs for OpenCL kernel co-execution in heterogeneous systems

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Heterogeneous systems have a very high potential performance but present difficulties in their programming. OmpSs is a well known framework for task based parallel applications, which is an interesting tool to simplify the programming of these systems. However, it does not support the co-execution of a single OpenCL kernel instance on several compute devices. To overcome this limitation, this paper presents an extension of the OmpSs framework that solves two main objectives: the automatic division of datasets among several devices and the management of their memory address spaces. To adapt to different kinds of applications, the data division can be performed by the novel HGuided load balancing algorithm or by the well known Static and Dynamic. All this is accomplished with negligible impact on the programming. Experimental results reveal that there is always one load balancing algorithm that improves the performance and energy consumption of the system.This work has been supported by the University of Cantabria with grant CVE-2014-18166, the Generalitat de Catalunya under grant 2014-SGR-1051, the Spanish Ministry of Economy, Industry and Competitiveness under contracts TIN2016- 76635-C2-2-R (AEI/FEDER, UE) and TIN2015-65316-P. The Spanish Government through the Programa Severo Ochoa (SEV-2015-0493). The European Research Council under grant agreement No 321253 European Community’s Seventh Framework Programme [FP7/2007-2013] and Horizon 2020 under the Mont-Blanc Projects, grant agreement n 288777, 610402 and 671697 and the European HiPEAC Network.Peer ReviewedPostprint (published version

Adaptive and architecture-independent task granularity for recursive applications

In the last few decades, modern applications have become larger and more complex. Among the users of these applications, the need to simplify the process of identifying units of work increased as well. With the approach of tasking models, this want has been satisfied. These models make scheduling units of work much more user-friendly. However, with the arrival of tasking models, came granularity management. Discovering an application’s optimal granularity is a frequent and sometimes challenging task for a wide range of recursive algorithms. Often, finding the optimal granularity will cause a substantial increase in performance. With that in mind, the quest for optimality is no easy task. Many aspects have to be considered that are directly related to lack or excess of parallelism in applications. There is no general solution as the optimal granularity depends on both algorithm and system characteristics. One commonly used method to find an optimal granularity consists in experimentally tuning an application with different granularities until an optimal is found. This paper proposes several heuristics which, combined with the appropriate monitoring techniques, allow a runtime system to automatically tune the granularity of recursive applications. The solution is independent of the architecture, execution environment or application being tested. A reference implementation in OmpSs—a task-parallel programming model—shows the programmability, ease of use and competitive performance of the proposed solution. Results show that the proposed solution is able to achieve, for any scenario, at least 75% of the performance of optimally tuned applications.This work has been supported by the Spanish Ministry of Science and Innovation (contract TIN2015-65316), the grant SEV-2015-0493 of Severo Ochoa Program awarded by the Spanish Government, and by Generalitat de Catalunya (contract 2014-SGR-1051)Peer ReviewedPostprint (author's final draft

Fatigue resistance evaluation of high Mn-TWIP steel through damage mechanics: A new method based on stiffness evolution

The work presented here deals with the implementation of a new methodology that allows fast and reliable determination of the fatigue strength. It is based on monitoring the specimen stiffness changes at different stress levels, as an indicator of the evolution of fatigue damage. This new rapid fatigue test uses techniques available in many laboratories, as the DIC (Digital Image Correlation) technique and common extensometers. Moreover, the obtained data are easier to handle than infrared cameras or acoustic emission systems data, and the experimental procedure to determine the fatigue limit is more evident than in the self-heating method. Experiments have been conducted in TWIP (Twinning Induced Plasticity) steel, a material used for lightweighting the structural parts of vehicles. With their excellent energy absorption capacity, TWIP steels can satisfy the part requirements in terms of crash performance, while their high tensile strength can deal with the cyclic loads acting on chassis parts. Therefore, many efforts focus on improving the fatigue strength of TWIP steels through pre-straining and/or surface treatments. However, finding the best way to improve the fatigue resistance requires time and resources that often hinder the development of the material. For this reason, a TWIP steel has been selected to check the new rapid fatigue test. The prediction made using the proposed approach is validated by comparison with conventional staircase results and fatigue crack growth standardised tests. The good agreement allows proposing the new method as a fast and efficient way to determine the fatigue resistance in metals.Peer ReviewedPostprint (published version

Extending the OpenCHK Model with Advanced Checkpoint Features

One of the major challenges in using extreme scale systems efficiently is to mitigate the impact of faults. Application-level checkpoint/restart (CR) methods provide the best trade-off between productivity, robustness, and performance. There are many solutions implementing CR at the application level. They all provide advanced I/O capabilities to minimize the overhead introduced by CR. Nevertheless, there is still room for improvement in terms of programmability and flexibility, because end-users must manually serialize and deserialize application state using low-level APIs, modify the flow of the application to consider restarts, or rewrite CR code whenever the backend library changes. In this work, we propose a set of compiler directives and clauses that allow users to specify CR operations in a simple way. Our approach supports the common CR features provided by all the CR libraries. However, it can also be extended to support advanced features that are only available in some CR libraries, such as differential checkpointing, the use of HDF5 format, and the possibility of using fault-tolerance-dedicated threads. The result of our evaluation revealed a high increase in programmability. On average, we reduced the number of lines of code by 71%, 94%, and 64% for FTI, SCR, and VeloC, respectively, and no additional overhead was perceived using our solution compared to using the backend libraries directly. Finally, portability is enhanced because our programming model allows the use of any backend library without changing any code

Understanding the fatigue notch sensitivity of high-strength steels through fracture toughness

This study presents an innovative approach for selecting high-strength materials for fatigue dimensioning parts, considering both fracture toughness and fatigue performance. Warm and hot forming processes enable the construction of high-strength parts above 1000 MPa with complex geometries, making them suitable for lightweight chassis in automotive and freight applications. This research reveals that high-strength steels can experience up to a 40% reduction in fatigue performance due to manufacturing defects introduced during punching and trimming. Fracture toughness has been proposed as a good indicator of notch sensitivity, with a strong correlation of 0.83 between fracture toughness and fatigue notch sensitivity. Therefore, by combining fracture toughness measurements and fatigue resistance obtained through the rapid fatigue test, it becomes possible to quickly identify the most fatigue-resistant materials to deal with defects. Among the nine materials analysed, warm-formed steels show promising characteristics for lightweight chassis construction, with high fatigue resistance and fracture toughness exceeding the proposed fracture threshold of 250 kJ/m2.Peer ReviewedPostprint (published version

Fracture toughness to assess the effect of trimming on the fatigue behaviour of high-strength steels for chassis parts

High-strength steels are widely used in vehicle body-in-white, offering a good balance between crashworthiness and lightweight design. The increased requirements of heavier electric vehicles, in terms of fatigue resistance and crashworthiness, highlight that chassis parts have remarkable lightweighting potential. However, applying these grades in chassis parts is not straightforward, as the forming processes, like trimming, may introduce surface defects that compromise the fatigue resistance of the component. This work presents a material selection strategy for the applicability of high-strength steels in chassis parts of electric vehicles. The proposed approach allows the evaluation of the key parameters of the chassis parts in a simple way. The crash performance is evaluated through fracture toughness using the essential work of fracture (EWF) methodology. The method is applied to thin high-strength steel sheets employing double-edge notched tensile specimens (DENT). On the other hand, fatigue performance is investigated in terms of fatigue resistance for both notched and unnotched specimens. The results for different complex-phase and dual-phase steels show a good agreement between the EWF and the fatigue notch factor. The method could help apply high-strength steel to chassis parts, as designers will have a tool to focus the expensive fatigue tests on the best material candidates.Postprint (published version

Worksharing tasks: An efficient way to exploit irregular and fine-grained loop parallelism

Shared memory programming models usually provide worksharing and task constructs. The former relies on the efficient fork-join execution model to exploit structured parallelism; while the latter relies on fine-grained synchronization among tasks and a flexible data-flow execution model to exploit dynamic, irregular, and nested parallelism. On applications that show both structured and unstructured parallelism, both worksharing and task constructs can be combined. However, it is difficult to mix both execution models without penalizing the data-flow execution model. Hence, on many applications structured parallelism is also exploited using tasks to leverage the full benefits of a pure data-flow execution model. However, task creation and management might introduce a non-negligible overhead that prevents the efficient exploitation of fine-grained structured parallelism, especially on many-core processors. In this work, we propose worksharing tasks. These are tasks that internally leverage worksharing techniques to exploit fine-grained structured loop-based parallelism. The evaluation shows promising results on several benchmarks and platforms.This work is supported by the Spanish Ministerio de Ciencia, Innovacion y Universidades (TIN2015-65316-P), by the Generalitat de Catalunya (2014-SGR-1051) and by the European Union’s Seventh Framework Programme (FP7/2007-2013) and the H2020 funding framework under grant agreement no. H2020-FETHPC-754304 (DEEP-EST).Peer ReviewedPostprint (author's final draft