GPU devices for safety-critical systems: a survey

Graphics Processing Unit (GPU) devices and their associated software programming languages and frameworks can deliver the computing performance required to facilitate the development of next-generation high-performance safety-critical systems such as autonomous driving systems. However, the integration of complex, parallel, and computationally demanding software functions with different safety-criticality levels on GPU devices with shared hardware resources contributes to several safety certification challenges. This survey categorizes and provides an overview of research contributions that address GPU devices’ random hardware failures, systematic failures, and independence of execution.This work has been partially supported by the European Research Council with Horizon 2020 (grant agreements No. 772773 and 871465), the Spanish Ministry of Science and Innovation under grant PID2019-107255GB, the HiPEAC Network of Excellence and the Basque Government under grant KK-2019-00035. The Spanish Ministry of Economy and Competitiveness has also partially supported Leonidas Kosmidis with a Juan de la Cierva Incorporación postdoctoral fellowship (FJCI-2020- 045931-I).Peer ReviewedPostprint (author's final draft

Quality Time: A simple online technique for quantifying multicore execution efficiency

Abstract—In order to increase utilization, multicore pro-cessors share memory resources among an increasing number of cores. This sharing leads to memory interference, which in turn leads to a non-uniform degradation in the execution of concurrent applications, even in the presence of fairness mechanisms. Many utilities rely on application CPU Time both for measuring resource usage and inferring application progress. These utilities are therefore directly affected by the distorting effects of multicore interference on the representativeness of CPU Time as a proxy for progress. This makes reasoning about myriad properties from fairness, to QoS, to throughput optimality very difficult in consolidated environments, such as IaaS. We introduce the notion of Quality Time, which provides a measure of application progress analogous to CPU Time’s measure of resource usage, and we propose a simple online sampling-based technique to approximate Quality Time with high accuracy. We have implemented three user-space tools called Qtime, Qtop, and Qplacer. Qtime can attach to an application to calculate its Quality Time online, Qtop is a dashboard that monitors the Quality Times of all applications on the system, and Qplacer leverages Quality Time information to find better application placements and improve overall system quality. With Quality Time, we are able to reduce the error in inferring execution efficiency from 150.3 % to 25.1 % in the worst case and from 30.0 % to 7.5 % on average. Qplacer can increase average system throughput by 3.2 % when compared to static application placement. I

Learning-based run-time power and energy management of multi/many-core systems: current and future trends

Multi/Many-core systems are prevalent in several application domains targeting different scales of computing such as embedded and cloud computing. These systems are able to fulfil the everincreasing performance requirements by exploiting their parallel processing capabilities. However, effective power/energy management is required during system operations due to several reasons such as to increase the operational time of battery operated systems, reduce the energy cost of datacenters, and improve thermal efficiency and reliability. This article provides an extensive survey of learning-based run-time power/energy management approaches. The survey includes a taxonomy of the learning-based approaches. These approaches perform design-time and/or run-time power/energy management by employing some learning principles such as reinforcement learning. The survey also highlights the trends followed by the learning-based run-time power management approaches, their upcoming trends and open research challenges

Energy Aware Runtime Systems for Elastic Stream Processing Platforms

Following an invariant growth in the required computational performance of processors, the multicore revolution started around 20 years ago. This revolution was mainly an answer to power dissipation constraints restricting the increase of clock frequency in single-core processors. The multicore revolution not only brought in the challenge of parallel programming, i.e. being able to develop software exploiting the entire capabilities of manycore architectures, but also the challenge of programming heterogeneous platforms. The question of “on which processing element to map a specific computational unit?”, is well known in the embedded community. With the introduction of general-purpose graphics processing units (GPGPUs), digital signal processors (DSPs) along with many-core processors on different system-on-chip platforms, heterogeneous parallel platforms are nowadays widespread over several domains, from consumer devices to media processing platforms for telecom operators. Finding mapping together with a suitable hardware architecture is a process called design-space exploration. This process is very challenging in heterogeneous many-core architectures, which promise to offer benefits in terms of energy efficiency. The main problem is the exponential explosion of space exploration. With the recent trend of increasing levels of heterogeneity in the chip, selecting the parameters to take into account when mapping software to hardware is still an open research topic in the embedded area. For example, the current Linux scheduler has poor performance when mapping tasks to computing elements available in hardware. The only metric considered is CPU workload, which as was shown in recent work does not match true performance demands from the applications. Doing so may produce an incorrect allocation of resources, resulting in a waste of energy. The origin of this research work comes from the observation that these approaches do not provide full support for the dynamic behavior of stream processing applications, especially if these behaviors are established only at runtime. This research will contribute to the general goal of developing energy-efficient solutions to design streaming applications on heterogeneous and parallel hardware platforms. Streaming applications are nowadays widely spread in the software domain. Their distinctive characiteristic is the retrieving of multiple streams of data and the need to process them in real time. The proposed work will develop new approaches to address the challenging problem of efficient runtime coordination of dynamic applications, focusing on energy and performance management.Efter en oföränderlig tillväxt i prestandakrav hos processorer, började den flerkärniga processor-revolutionen för ungefär 20 år sedan. Denna revolution skedde till största del som en lösning till begränsningar i energieffekten allt eftersom klockfrekvensen kontinuerligt höjdes i en-kärniga processorer. Den flerkärniga processor-revolutionen medförde inte enbart utmaningen gällande parallellprogrammering, m.a.o. förmågan att utveckla mjukvara som använder sig av alla delelement i de flerkärniga processorerna, men också utmaningen med programmering av heterogena plattformar. Frågeställningen ”på vilken processorelement skall en viss beräkning utföras?” är väl känt inom ramen för inbyggda datorsystem. Efter introduktionen av grafikprocessorer för allmänna beräkningar (GPGPU), signalprocesserings-processorer (DSP) samt flerkärniga processorer på olika system-on-chip plattformar, är heterogena parallella plattformar idag omfattande inom många domäner, från konsumtionsartiklar till mediaprocesseringsplattformar för telekommunikationsoperatörer. Processen att placera beräkningarna på en passande hårdvaruplattform kallas för utforskning av en designrymd (design-space exploration). Denna process är mycket utmanande för heterogena flerkärniga arkitekturer, och kan medföra fördelar när det gäller energieffektivitet. Det största problemet är att de olika valmöjligheterna i designrymden kan växa exponentiellt. Enligt den nuvarande trenden som förespår ökad heterogeniska aspekter i processorerna är utmaningen att hitta den mest passande placeringen av beräkningarna på hårdvaran ännu en forskningsfråga inom ramen för inbyggda datorsystem. Till exempel, den nuvarande schemaläggaren i Linux operativsystemet är inkapabel att hitta en effektiv placering av beräkningarna på den underliggande hårdvaran. Det enda mätsättet som används är processorns belastning vilket, som visats i tidigare forskning, inte motsvarar den verkliga prestandan i applikationen. Användning av detta mätsätt vid resursallokering resulterar i slöseri med energi. Denna forskning härstammar från observationerna att dessa tillvägagångssätt inte stöder det dynamiska beteendet hos ström-processeringsapplikationer (stream processing applications), speciellt om beteendena bara etableras vid körtid. Denna forskning kontribuerar till det allmänna målet att utveckla energieffektiva lösningar för ström-applikationer (streaming applications) på heterogena flerkärniga hårdvaruplattformar. Ström-applikationer är numera mycket vanliga i mjukvarudomän. Deras distinkta karaktär är inläsning av flertalet dataströmmar, och behov av att processera dem i realtid. Arbetet i denna forskning understöder utvecklingen av nya sätt för att lösa det utmanade problemet att effektivt koordinera dynamiska applikationer i realtid och fokus på energi- och prestandahantering

Development and certification of mixed-criticality embedded systems based on probabilistic timing analysis

An increasing variety of emerging systems relentlessly replaces or augments the functionality of mechanical subsystems with embedded electronics. For quantity, complexity, and use, the safety of such subsystems is an increasingly important matter. Accordingly, those systems are subject to safety certification to demonstrate system's safety by rigorous development processes and hardware/software constraints. The massive augment in embedded processors' complexity renders the arduous certification task significantly harder to achieve. The focus of this thesis is to address the certification challenges in multicore architectures: despite their potential to integrate several applications on a single platform, their inherent complexity imperils their timing predictability and certification. Recently, the Measurement-Based Probabilistic Timing Analysis (MBPTA) technique emerged as an alternative to deal with hardware/software complexity. The innovation that MBPTA brings about is, however, a major step from current certification procedures and standards. The particular contributions of this Thesis include: (i) the definition of certification arguments for mixed-criticality integration upon multicore processors. In particular we propose a set of safety mechanisms and procedures as required to comply with functional safety standards. For timing predictability, (ii) we present a quantitative approach to assess the likelihood of execution-time exceedance events with respect to the risk reduction requirements on safety standards. To this end, we build upon the MBPTA approach and we present the design of a safety-related source of randomization (SoR), that plays a key role in the platform-level randomization needed by MBPTA. And (iii) we evaluate current certification guidance with respect to emerging high performance design trends like caches. Overall, this Thesis pushes the certification limits in the use of multicore and MBPTA technology in Critical Real-Time Embedded Systems (CRTES) and paves the way towards their adoption in industry.Una creciente variedad de sistemas emergentes reemplazan o aumentan la funcionalidad de subsistemas mecánicos con componentes electrónicos embebidos. El aumento en la cantidad y complejidad de dichos subsistemas electrónicos así como su cometido, hacen de su seguridad una cuestión de creciente importancia. Tanto es así que la comercialización de estos sistemas críticos está sujeta a rigurosos procesos de certificación donde se garantiza la seguridad del sistema mediante estrictas restricciones en el proceso de desarrollo y diseño de su hardware y software. Esta tesis trata de abordar los nuevos retos y dificultades dadas por la introducción de procesadores multi-núcleo en dichos sistemas críticos: aunque su mayor rendimiento despierta el interés de la industria para integrar múltiples aplicaciones en una sola plataforma, suponen una mayor complejidad. Su arquitectura desafía su análisis temporal mediante los métodos tradicionales y, asimismo, su certificación es cada vez más compleja y costosa. Con el fin de lidiar con estas limitaciones, recientemente se ha desarrollado una novedosa técnica de análisis temporal probabilístico basado en medidas (MBPTA). La innovación de esta técnica, sin embargo, supone un gran cambio cultural respecto a los estándares y procedimientos tradicionales de certificación. En esta línea, las contribuciones de esta tesis están agrupadas en tres ejes principales: (i) definición de argumentos de seguridad para la certificación de aplicaciones de criticidad-mixta sobre plataformas multi-núcleo. Se definen, en particular, mecanismos de seguridad, técnicas de diagnóstico y reacción de faltas acorde con el estándar IEC 61508 sobre una arquitectura multi-núcleo de referencia. Respecto al análisis temporal, (ii) presentamos la cuantificación de la probabilidad de exceder un límite temporal y su relación con los requisitos de reducción de riesgos derivados de los estándares de seguridad funcional. Con este fin, nos basamos en la técnica MBPTA y presentamos el diseño de una fuente de números aleatorios segura; un componente clave para conseguir las propiedades aleatorias requeridas por MBPTA a nivel de plataforma. Por último, (iii) extrapolamos las guías actuales para la certificación de arquitecturas multi-núcleo a una solución comercial de 8 núcleos y las evaluamos con respecto a las tendencias emergentes de diseño de alto rendimiento (caches). Con estas contribuciones, esta tesis trata de abordar los retos que el uso de procesadores multi-núcleo y MBPTA implican en el proceso de certificación de sistemas críticos de tiempo real y facilita, de esta forma, su adopción por la industria.Postprint (published version

System software techniques to enhance reliability of modern platforms

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Uncertainty Aware Mapping of Embedded Systems for Reliability, Performance, and Energy

Due to technology downscaling, embedded systems have increased in complexity and heterogeneity. The increasingly large process, voltage, and temperature variations negatively affect the design and optimization process of these systems. These factors contribute to increased uncertainties that in turn undermine the accuracy and effectiveness of traditional design approaches. In this thesis, we formulate the problem of uncertainty aware mapping for multicore embedded system platforms as a multi-objective optimization problem. We present a solution to this problem that integrates uncertainty models as a new design methodology constructed with Monte Carlo and evolutionary algorithms. The solution is uncertainty aware because it is able to model uncertainties in design parameters and to identify robust design points that limit the influence of these uncertainties onto the objective functions. The proposed design methodology is implemented as a tool that can generate the robust Pareto frontier in the objective space formed by reliability, performance, and energy consumption