Improving time predictability of shared hardware resources in real-time multicore systems : emphasis on the space domain

Critical Real-Time Embedded Systems (CRTES) follow a verification and validation process on the timing and functional correctness. This process includes the timing analysis that provides Worst-Case Execution Time (WCET) estimates to provide evidence that the execution time of the system, or parts of it, remain within the deadlines. A key design principle for CRTES is the incremental qualification, whereby each software component can be subject to verification and validation independently of any other component, with obvious benefits for cost. At timing level, this requires time composability, such that the timing behavior of a function is not affected by other functions. CRTES are experiencing an unprecedented growth with rising performance demands that have motivated the use of multicore architectures. Multicores can provide the performance required and bring the potential of integrating several software functions onto the same hardware. However, multicore contention in the access to shared hardware resources creates a dependence of the execution time of a task with the rest of the tasks running simultaneously. This dependence threatens time predictability and jeopardizes time composability. In this thesis we analyze and propose hardware solutions to be applied on current multicore designs for CRTES to improve time predictability and time composability, focusing on the on-chip bus and the memory controller. At hardware level, we propose new bus and memory controller designs that control and mitigate contention between different cores and allow to have time composability by design, also in the context of mixed-criticality systems. At analysis level, we propose contention prediction models that factor the impact of contenders and don¿t need modifications to the hardware. We also propose a set of Performance Monitoring Counters (PMC) that provide evidence about the contention. We give an special emphasis on the Space domain focusing on the Cobham Gaisler NGMP multicore processor, which is currently assessed by the European Space Agency for its future missions.Los Sistemas Críticos Empotrados de Tiempo Real (CRTES) siguen un proceso de verificación y validación para su correctitud funcional y temporal. Este proceso incluye el análisis temporal que proporciona estimaciones de el peor caso del tiempo de ejecución (WCET) para dar evidencia de que el tiempo de ejecución del sistema, o partes de él, permanecen dentro de los límites temporales. Un principio de diseño clave para los CRTES es la cualificación incremental, por la que cada componente de software puede ser verificado y validado independientemente del resto de componentes, con beneficios obvios para el coste. A nivel temporal, esto requiere composabilidad temporal, por la que el comportamiento temporal de una función no se ve afectado por otras funciones. CRTES están experimentando un crecimiento sin precedentes con crecientes demandas de rendimiento que han motivado el uso the arquitecturas multi-núcleo (multicore). Los procesadores multi-núcleo pueden proporcionar el rendimiento requerido y tienen el potencial de integrar varias funcionalidades software en el mismo hardware. A pesar de ello, la interferencia entre los diferentes núcleos que aparece en los recursos compartidos de os procesadores multi núcleo crea una dependencia del tiempo de ejecución de una tarea con el resto de tareas ejecutándose simultáneamente en el procesador. Esta dependencia amenaza la predictabilidad temporal y compromete la composabilidad temporal. En esta tésis analizamos y proponemos soluciones hardware para ser aplicadas en los diseños multi núcleo actuales para CRTES que mejoran la predictabilidad y composabilidad temporal, centrándose en el bus y el controlador de memoria internos al chip. A nivel de hardware, proponemos nuevos diseños de buses y controladores de memoria que controlan y mitigan la interferencia entre los diferentes núcleos y permiten tener composabilidad temporal por diseño, también en el contexto de sistemas de criticalidad mixta. A nivel de análisis, proponemos modelos de predicción de la interferencia que factorizan el impacto de los núcleos y no necesitan modificaciones hardware. También proponemos un conjunto de Contadores de Control del Rendimiento (PMC) que proporcionoan evidencia de la interferencia. En esta tésis, damós especial importancia al dominio espacial, centrándonos en el procesador mutli núcleo Cobham Gaisler NGMP, que está siendo actualmente evaluado por la Agencia Espacial Europea para sus futuras misiones

Automatic generation of synthetic workloads for multicore systems

textWhen designing a computer system, benchmark programs are used with cycle accurate performance/power simulators and HDL level simulators to evaluate novel architectural enhancements, perform design space exploration, understand the worst-case power characteristics of various designs and find performance bottlenecks. This research effort is directed towards automatically generating synthetic benchmarks to tackle three design challenges: 1) For most of the simulation related purposes, full runs of modern real world parallel applications like the PARSEC, SPLASH suites cannot be used as they take machine weeks of time on cycle accurate and HDL level simulators incurring a prohibitively large time cost 2) The second design challenge is that, some of these real world applications are intellectual property and cannot be shared with processor vendors for design studies 3) The most significant problem in the design stage is the complexity involved in fixing the maximum power consumption of a multicore design, called the Thermal Design Power (TDP). In an effort towards fixing this maximum power consumption of a system at the most optimal point, designers are used to hand-crafting possible code snippets called power viruses. But, this process of trying to manually write such maximum power consuming code snippets is very tedious. All of these aforementioned challenges has lead to the resurrection of synthetic benchmarks in the recent past, serving as a promising solution to all the challenges. During the design stage of a multicore system, availability of a framework to automatically generate system-level synthetic benchmarks for multicore systems will greatly simplify the design process and result in more confident design decisions. The key idea behind such an adaptable benchmark synthesis framework is to identify the key characteristics of real world parallel applications that affect the performance and power consumption of a real program and create synthetic executable programs by varying the values for these characteristics. Firstly, with such a framework, one can generate miniaturized synthetic clones for large target (current and futuristic) parallel applications enabling an architect to use them with slow low-level simulation models (e.g., RTL models in VHDL/Verilog) and helps in tailoring designs to the targeted applications. These synthetic benchmark clones can be distributed to architects and designers even if the original applications are intellectual property, when they are not publicly available. Lastly, such a framework can be used to automatically create maximum power consuming code snippets to be able to help in fixing the TDP, heat sinks, cooling system and other power related features of the system. The workload cloning framework built using the proposed synthetic benchmark generation methodology is evaluated to show its superiority over the existing cloning methodologies for single-core systems by generating miniaturized clones for CPU2006 and ImplantBench workloads with only an average error of 2.9% in performance for up to five orders of magnitude of simulation speedup. The correlation coefficient predicting the sensitivity to design changes is 0.95 and 0.98 for performance and power consumption. The proposed framework is evaluated by cloning parallel applications implemented based on p-threads and OpenMP in the PARSEC benchmark suite. The average error in predicting performance is 4.87% and that of power consumption is 2.73%. The correlation coefficient predicting the sensitivity to design changes is 0.92 for performance. The efficacy of the proposed synthetic benchmark generation framework for power virus generation is evaluation on SPARC, Alpha and x86 ISAs using full system simulators and also using real hardware. The results show that the power viruses generated for single-core systems consume 14-41% more power compared to MPrime on SPARC ISA. Similarly, the power viruses generated for multicore systems consume 45-98%, 40-89% and 41-56% more power than PARSEC workloads, running multiple copies of MPrime and multithreaded SPECjbb respectively.Electrical and Computer Engineerin

Planificación consciente de la contención y gestión de recursos en arquitecturas multicore emergentes

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Arquitectura de Computadores y Automática, leída el 14-12-2021Chip multicore processors (CMPs) currently constitute the architecture of choice for mosto general-pùrpose computing systems, and they will likely continue to be dominant in the near future. Advances in technology have enabled to pack an increasing number of cores and bigger caches on the same chip. Nevertheless, contention on shared resources on CMPs -present since the advent of these architectures- still poses a big challenge. Cores in a CMP typically share a last-level cache (LLC) and other memory-related resources with the remaining cores, such as a DRAM controller and an interconnection network. This causes that co-running applications may intensively compete with each other for these shared resources, leading to substantial and uneven performance degradation...Los procesadores multinúcleo o CMPs (Chip Multicore Processors) son actualmente la arquitectura más usada por la mayoría de sistemas de computación de propósito general, y muy probablemente se mantendrían en esa posición dominante en el futuro cercano. Los avances tecnológicos han permitido integrar progresivamente en el mismo chip más cores y aumentar los tamaños de los distintos niveles de cache. No obstante, la contención de recursos compartidos en CMPs {presente desde la aparición de estas arquitecturas{ todavía representa un reto importante que afrontar. Los cores en un CMP comparten en la mayor parte de los diseños una cache de último nivel o LLC (Last-Level Cache) y otros recursos, como el controlador de DRAM o una red de interconexión. La existencia de dichos recursos compartidos provoca en ocasiones que cuando se ejecutan dos o más aplicaciones simultáneamente en el sistema, se produzca una degradación sustancial y potencialmente desigual del rendimiento entre aplicaciones...Fac. de InformáticaTRUEunpu

Smart hardware designs for probabilistically-analyzable processor architectures

Future Critical Real-Time Embedded Systems (CRTES), like those is planes, cars or trains, require more and more guaranteed performance in order to satisfy the increasing performance demands of advanced complex software features. While increased performance can be achieved by deploying processor techniques currently used in High-Performance Computing (HPC) and mainstream domains, their use challenges the software timing analysis, a necessary step in CRTES' verification and validation. Cache memories are known to have high impact in performance, and in fact, current CRTES include multicores usually with several levels of cache. In this line, this Thesis aims at increasing the guaranteed performance of CRTES by using techniques for caches building upon time randomization and providing probabilistic guarantees of tasks' execution time. In this Thesis, we first focus on on improving cache placement and replacement to improve guaranteed performance. For placement, different existing policies are explored in a multi-level cache setup, and a solution is reached in which different of those policies are combined. For cache replacement, we analyze a pathological scenario that no cache policy so far accounts and propose several policies that fix this pathological scenario. For shared caches in multicore we observe that contention is mainly caused by private writes that go through to the shared cache, yet using a pure write-back policy also has its drawbacks. We propose a hybrid approach to mitigate this contention. Building on this solution, the next contribution tackles a problem caused by the need of some reliability mechanisms in CRTES. Implementing reliability close to the processor's core has a significant impact in performance. A look-ahead error detection solution is proposed to greatly mitigate the performance impact. The next contribution proposes the first hardware prefetcher for CRTES with arbitrary cache hierarchies. Given its speculative nature, prefetchers that have a guaranteed positive impact on performance are difficult to design. We present a framework that provides execution time guarantees and obtains a performance benefit. Finally, we focus on the impact of timing anomalies in CRTES with caches. For the first time, a definition and taxonomy of timing anomalies is given for Measurement-Based Timing Analysis. Then, we focus on a specific timing anomaly that can happen with caches and provide a solution to account for it in the execution time estimates.Los Sistemas Empotrados de Tiempo-Real Crítico (SETRC), como los de los aviones, coches o trenes, requieren más y más rendimiento garantizado para satisfacer la demanda al alza de rendimiento para funciones complejas y avanzadas de software. Aunque el incremento en rendimiento puede ser adquirido utilizando técnicas de arquitectura de procesadores actualmente utilizadas en la Computación de Altas Prestaciones (CAP) i en los dominios convencionales, este uso presenta retos para el análisis del tiempo de software, un paso necesario en la verificación y validación de SETRC. Las memorias caches son conocidas por su gran impacto en rendimiento y, de hecho, los actuales SETRC incluyen multicores normalmente con diversos niveles de cache. En esta línea, esta Tesis tiene como objetivo mejorar el rendimiento garantizado de los SETRC utilizando técnicas para caches y utilizando métodos como la randomización del tiempo y proveyendo garantías probabilísticas de tiempo de ejecución de las tareas. En esta Tesis, primero nos centramos en mejorar la colocación y el reemplazo de caches para mejorar el rendimiento garantizado. Para la colocación, diferentes políticas son exploradas en un sistema cache multi-nivel, y se llega a una solución donde diversas de estas políticas son combinadas. Para el reemplazo, analizamos un escenario patológico que ninguna política actual tiene en cuenta, y proponemos varias políticas que solucionan este escenario patológico. Para caches compartidas en multicores, observamos que la contención es causada principalmente por escrituras privadas que van a través de la cache compartida, pero usar una política de escritura retardada pura también tiene sus consecuencias. Proponemos un enfoque híbrido para mitigar la contención. Sobre esta solución, la siguiente contribución ataca un problema causado por la necesidad de mecanismos de fiabilidad en SETRC. Implementar fiabilidad cerca del núcleo del procesador tiene un impacto significativo en rendimiento. Una solución basada en anticipación se propone para mitigar el impacto en rendimiento. La siguiente contribución propone el primer prefetcher hardware para SETRC con una jerarquía de caches arbitraria. Por primera vez, se da una definición y taxonomía de anomalías temporales para Análisis Temporal Basado en Medidas. Después, nos centramos en una anomalía temporal concreta que puede pasar con caches y ofrecemos una solución que la tiene en cuenta en las estimaciones del tiempo de ejecución.Postprint (published version

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

Operating System Kernels on Multi-core Architectures

Operating System (OS) kernels have been under research and development for decades, mainly assuming single processor and distributed hardware systems. With the recent rise of multi-core chips that may incorporate a network on chip (NoC), new challenges have appeared that were not considered before. Given that a complete multi-core system that works on a single system on chip (SoC) is now the normal case, different cores on a single SoC may share other physical resources and data. This new sharing scheme on a SoC affects crucial aspects of an overall system like correctness, performance, predictability, scalability and security. Both hardware and OSs to flexibly cooperate in order to provide solutions for such challenges. SoC mimics the internet somehow now, with different cores acting as computer nodes, and the network medium is given in an advanced digital fabrics like buses or NoCs, that are a current research area. However, OSs are still assuming some (hardware) features like single physical memory and memory sharing for inter-process communication, page-based protection, cache operations, even when evolving from uniprocessor to multi-core processors. Such features not only may degrade performance and other system aspects, but also some of them make no sense for a multi-core SoC, and introduce some barriers and limitations. While new OS research is considering different kernel designs to cope up with multi-core systems, they are still limited by the current commercial hardware architectures. The objective of this thesis is to assess different kernel designs and implementations on multi-core hardware architectures. Part of the contributions of the thesis is porting RTEMS (RTOS) and seL4 microkernel to Epiphany and RISC-V hardware architectures respectively, trading-off the design and implementation decisions. This hands-on experience gave a better understanding of the real-world challenges regarding kernel designs and implementations

High Performance Embedded Computing

Nowadays, the prevalence of computing systems in our lives is so ubiquitous that we live in a cyber-physical world dominated by computer systems, from pacemakers to cars and airplanes. These systems demand for more computational performance to process large amounts of data from multiple data sources with guaranteed processing times. Actuating outside of the required timing bounds may cause the failure of the system, being vital for systems like planes, cars, business monitoring, e-trading, etc. High-Performance and Time-Predictable Embedded Computing presents recent advances in software architecture and tools to support such complex systems, enabling the design of embedded computing devices which are able to deliver high-performance whilst guaranteeing the application required timing bounds. Technical topics discussed in the book include: Parallel embedded platforms Programming models Mapping and scheduling of parallel computations Timing and schedulability analysis Runtimes and operating systemsThe work reflected in this book was done in the scope of the European project P SOCRATES, funded under the FP7 framework program of the European Commission. High-performance and time-predictable embedded computing is ideal for personnel in computer/communication/embedded industries as well as academic staff and master/research students in computer science, embedded systems, cyber-physical systems and internet-of-things

High-Performance and Time-Predictable Embedded Computing

Nowadays, the prevalence of computing systems in our lives is so ubiquitous that we live in a cyber-physical world dominated by computer systems, from pacemakers to cars and airplanes. These systems demand for more computational performance to process large amounts of data from multiple data sources with guaranteed processing times. Actuating outside of the required timing bounds may cause the failure of the system, being vital for systems like planes, cars, business monitoring, e-trading, etc. High-Performance and Time-Predictable Embedded Computing presents recent advances in software architecture and tools to support such complex systems, enabling the design of embedded computing devices which are able to deliver high-performance whilst guaranteeing the application required timing bounds. Technical topics discussed in the book include: Parallel embedded platforms Programming models Mapping and scheduling of parallel computations Timing and schedulability analysis Runtimes and operating systems The work reflected in this book was done in the scope of the European project P SOCRATES, funded under the FP7 framework program of the European Commission. High-performance and time-predictable embedded computing is ideal for personnel in computer/communication/embedded industries as well as academic staff and master/research students in computer science, embedded systems, cyber-physical systems and internet-of-things.info:eu-repo/semantics/publishedVersio

Design Space Exploration and Resource Management of Multi/Many-Core Systems

The increasing demand of processing a higher number of applications and related data on computing platforms has resulted in reliance on multi-/many-core chips as they facilitate parallel processing. However, there is a desire for these platforms to be energy-efficient and reliable, and they need to perform secure computations for the interest of the whole community. This book provides perspectives on the aforementioned aspects from leading researchers in terms of state-of-the-art contributions and upcoming trends