Numerical simulation of sea waves and their impact against breakwaters for assessing coastal protection systems

Aquest treball estudia la propagació d’ones i la seva interacció amb estructures sòlides utilitzant un innovador mètode numèric, el Particle Finite Element Method (PFEM). Un mètode numèric és un model de simulació equivalent a un físic capaç de recrear la realitat. Per validar el mètode numèric a l’àrea d’aplicació, aquest projecte compara els resultats obtinguts en PFEM amb resultats experimentals d’anàlisis a laboratoris. També els compara amb resultats d’un altre mètode numèric, el Eulerià Finite Element Method (FEM). Per fer-ho, quatre diferents anàlisis es duen a terme. Els dos primers estudiant el cas d’ones solitàries, el tercer estudia un tren d’ones i el Quart analitza un tren d’ones que impacta amb un trencaonades.Este trabajo estudia la propagación de olas y su interacción con estructuras sólidas usando un innovador método numérico, el Particle Finite Element Method (PFEM). Un método numérico es un modelo de simulación equivalente a uno físico capaz de recrear la realidad. Para validar el método numérico en el área de aplicación, este proyecto compara los resultados obtenidos en PFEM con resultados experimentales de análisis en laboratorios. También los compara con resultados de otro método numérico, el Euleriano Finite Element Method (FEM). Para hacerlo, cuatro diferentes análisis se llevan a cabo. Los dos primeros estudian el caso de olas solitarias, el tercero estudia un tren de olas y el cuarto analiza un tren de olas que impacta en un rompeolas.This work studies water waves propagation and their interaction with solid structures using an innovative numerical method, the Particle Finite Element Method (PFEM). A numerical method is a simulation model equivalent to a physical one able of simulating reality. To validate the numerical method in the given area of application, this project compares the results obtained by PFEM with experimental results from laboratory analysis. It also compares the results with the ones conducted with another numerical method, the Eulerian Finite Element Method (FEM). To do so, four different analyses are performed. The first two analyse the case of solitary waves, the third analyse a wave train and the fourth anayse a wave train that impacts with a breakwater

SafeTI Traffic Injector Enhancement for Effective Interference Testing in Critical Real-Time Systems

Safety-critical domains, such as automotive, space, and robotics, are adopting increasingly powerful multicores with abundant hardware shared resources for higher performance and efficiency. However, mutual interference due to parallel operation within the SoC must be properly validated. Recently, the SafeTI traffic injector has been released and integrated in a homogeneous RISC-V multicore for testing, otherwise untestable casuistic for software-only solutions. This paper introduces some enhancements performed on the SafeTI, which include internal pipelining for higher-rate traffic injection, and its tailoring to multiple interfaces, as well as its integration in a more powerful heterogeneous RISC-V multicore based on Gaisler's technology for the space domain.Comment: Abstract from the RISC-V Summit, June 2023, Barcelona (Spain

High-Integrity GPU Designs for Critical Real-Time Automotive Systems

Autonomous Driving (AD) imposes the use of highperformance hardware, such as GPUs, to perform object recognition and tracking in real-time. However, differently to the consumer electronics market, critical real-time AD functionalities require a high degree of resilience against faults, in line with the automotive ISO26262 functional safety standard requirements. ISO26262 imposes the use of some source of independent redundancy for the most critical functionalities so that a single fault cannot lead to a failure, being dual core lockstep (DCLS) with diversity the preferred choice for computing devices. Unfortunately, GPUs do not support diverse DCLS by construction, thus failing to meet ISO26262 requirements efficiently. In this paper we propose lightweight modifications to GPUs to enable diverse DCLS for critical real-time applications without diminishing their performance for non-critical applications. In particular, we show how enabling specific mechanisms for software-controlled kernel scheduling in the GPU, allows guaranteeing that redundant kernels can be executed in different resources so that a single fault cannot lead to a failure, as imposed by ISO26262. Our results on a GPU simulator and an NVIDIA GPU prove the viability of the approach and its effectiveness on high-performance GPU designs needed for AD systems.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Carles Hernandez is jointly funded by the MINECO and FEDER funds through grant TIN2014-60404-JIN.SíPostprint (author's final draft

An approach to quantifying hardware diversity against common cause failures

In this thesis, we cover the gapof quantifying diversity by introducing DIMP, a low-cost diversity metric based on analyzing the paths of the circuits and relating it to the particular case of automotive microcontrollers that implement lockstep cores

Genòmica Computacional

En aquest projecte es desenvolupa una aplicació paral·lela que construeix un Suffix Tree per tal de buscar les mutacions somàtiques d'un pacient. També s'utilitza aquesta estructura per tal de fer un estudi de genètica de poblacions.This project is developed a parallel application that constructs a Suffix Tree to search for the somatic mutations in a patient. This structure is also used to make a study of population genetics

Safety-related challenges and opportunities for GPUs in the automotive domain

GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as the reference computing solution for AD, with the emphasis in ISO 26262 functional safety requirements.Authors would like to thank Guillem Bernat from Rapita Systems for his technical feedback on this work. The research leading to this work has received funding from the European Re-search Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773). This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Carles Hernández is jointly funded by the Spanish Ministry of Economy and Competitiveness and FEDER funds through grant TIN2014-60404-JIN.Peer ReviewedPostprint (author's final draft

Software-only diverse redundancy on GPUs for autonomous driving platforms

Autonomous driving (AD) builds upon high-performance computing platforms including (1) general purpose CPUs as well as (2) specific accelerators, being GPUs one of the main representatives. Microcontrollers have reached ASIL-D compliance by implementing diverse redundancy with lockstep execution. However, ASIL-D compliant GPUs rely on either fully redundant lockstep GPUs (i.e. 2 GPUs), which doubles hardware costs, or fully redundant systems with a GPU and another accelerator, which virtually doubles design and validation/verification (V&V) costs. In this paper we analyze the degree of diversity achieved when implementing redundancy on a single GPU, showing that diverse redundancy is not achieved in many cases, and propose software strategies that guarantee achieving diverse redundancy for any kernel on systems using commercial off-the-shelf (COTS) GPUs, thus showing how to achieve ASIL-D compliance on a single COTS GPU in controlled scenarios.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC2013-14717Peer ReviewedPostprint (author's final draft

Software-only triple diverse redundancy on GPUs for autonomous driving platforms

Autonomous driving (AD) imposes the need for safe computations in high-performance computing (HPC) components such as GPUs, thus with capabilities to detect and recover from errors since a safe state may not exist anymore. This can be achieved with Triple Modular Redundancy (TMR) for computation components. Furthermore, error detection capabilities need to provide some form of diversity to avoid the case where a single fault leads all redundant executions lead to the same error, which would go undetected. In our past work, we assessed GPUs against dual modular redundancy (DMR) with diversity, showing their potential and limitations to provide diverse redundancy building on reset and restart for recovery. However, such recovery scheme may be too slow for some applications. This paper proposes a software-only solution to deliver diverse TMR on commercial off-the-shelf (COTS) GPUs. Our work details how staggered execution can be achieved and assesses the performance of TMR on COTS GPUs. Moreover, we identify those elements where diversity cannot be guaranteed and provide some discussion comparing the case of DMR and TMR for those elements.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871467 (SELENE). Leonidas Kosmidis has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under a Juan de la Cierva Formacion postdoctoral fellowship with number FJCI-2017-34095.Peer ReviewedPostprint (author's final draft

Analysis of Kernel Redundancy for Soft Error Mitigation on Embedded GPUs

The use of state-of-the-art commercial processors such as graphical processing units (GPUs) is becoming increasingly common in the New Space industry in order to ensure high performance and power efficiency. However, commercial GPUs are not designed to operate in a harsh environment and therefore different protection techniques need to be applied to mitigate the effects of radiation, including those produced by single events. This paper assesses the effectiveness of redundant kernel execution on tightly constrained embedded GPUs under proton irradiation, with results suggesting a significant improvement in the SDC cross-section without penalizing the stability of the whole system. In addition, the posterior error analysis shows that the CPU is the source of the majority of the events, which are mainly dominated by functional interrupts.This work has been supported by the Spanish Ministry of Science and Innovation as part of the PID2019-106455GB-C22 project

Envisioning a Safety Island to Enable HPC Devices in Safety-Critical Domains

HPC (High Performance Computing) devices increasingly become the only alternative to deliver the performance needed in safety-critical autonomous systems (e.g., autonomous cars, unmanned planes) due to deploying large and powerful multicores along with accelerators such as GPUs. However, the support that those HPC devices offer to realize safety-critical systems on top is heterogeneous. Safety islands have been devised to be coupled to HPC devices and complement them to meet the safety requirements of an increased set of applications, yet the variety of concepts and realizations is large. This paper presents our own concept of a safety island with two goals in mind: (1) offering a wide set of features to enable the broadest set of safety applications for each HPC device, and (2) being realized with open source components based on RISC-V ISA to ease its use and adoption. In particular, we present our safety island concept, the key features we foresee it should include, and its potential application beyond safety.Comment: White pape