Performance analysis and optimization of automotive GPUs

© 2019 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.Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) have drastically increased the performance demands of automotive systems. Suitable highperformance platforms building upon Graphic Processing Units (GPUs) have been developed to respond to this demand, being NVIDIA Jetson TX2 a relevant representative. However, whether high-performance GPU configurations are appropriate for automotive setups remains as an open question. This paper aims at providing light on this question by modelling an automotive GPU (Jetson TX2), analyzing its microarchitectural parameters against relevant benchmarks, and identifying specific configurations able to meaningfully increase performance within similar cost envelopes, or to decrease costs preserving original performance levels. Overall, our analysis opens the door to the optimization of automotive GPUs for further system efficiency.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant TIN2015-65316-P, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 772773) and the HiPEAC Network of Excellence. Pedro Benedicte and Jaume Abella have been partially supported by the MINECO under FPU15/01394 grant and Ramon y Cajal postdoctoral fellowship number RYC-2013-14717 respectively and Leonidas Kosmidis under Juan de la Cierva-Formacin postdoctoral fellowship (FJCI-2017-34095).Peer ReviewedPostprint (author's final draft

Improving early design stage timing modeling in multicore based real-time systems

This paper presents a modelling approach for the timing behavior of real-time embedded systems (RTES) in early design phases. The model focuses on multicore processors - accepted as the next computing platform for RTES - and in particular it predicts the contention tasks suffer in the access to multicore on-chip shared resources. The model presents the key properties of not requiring the application's source code or binary and having high-accuracy and low overhead. The former is of paramount importance in those common scenarios in which several software suppliers work in parallel implementing different applications for a system integrator, subject to different intellectual property (IP) constraints. Our model helps reducing the risk of exceeding the assigned budgets for each application in late design stages and its associated costs.This work has received funding from the European Space Agency under Project Reference AO=17722=13=NL=LvH, and has also been supported by the Spanish Ministry of Science and Innovation grant TIN2015-65316-P. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.Peer ReviewedPostprint (author's final draft

Design and development of auxiliary components for a new two-stroke, stratified-charge, lean-burn gasoline engine

A unique stepped-piston engine was developed by a group of research engineers at Universiti Teknologi Malaysia (UTM), from 2003 to 2005. The development work undertaken by them engulfs design, prototyping and evaluation over a predetermined period of time which was iterative and challenging in nature. The main objective of the program is to demonstrate local R&D capabilities on small engine work that is able to produce mobile powerhouse of comparable output, having low-fuel consumption and acceptable emission than its crankcase counterpart of similar displacement. A two-stroke engine work was selected as it posses a number of technological challenges, increase in its thermal efficiency, which upon successful undertakings will be useful in assisting the group in future powertrain undertakings in UTM. In its carbureted version, the single-cylinder aircooled engine incorporates a three-port transfer system and a dedicated crankcase breather. These features will enable the prototype to have high induction efficiency and to behave very much a two-stroke engine but equipped with a four-stroke crankcase lubrication system. After a series of analytical work the engine was subjected to a series of laboratory trials. It was also tested on a small watercraft platform with promising indication of its flexibility of use as a prime mover in mobile platform. In an effort to further enhance its technology features, the researchers have also embarked on the development of an add-on auxiliary system. The system comprises of an engine control unit (ECU), a directinjector unit, a dedicated lubricant dispenser unit and an embedded common rail fuel unit. This support system was incorporated onto the engine to demonstrate the finer points of environmental-friendly and fuel economy features. The outcome of this complete package is described in the report, covering the methodology and the final characteristics of the mobile power plant

A time-predictable many-core processor design for critical real-time embedded systems

Critical Real-Time Embedded Systems (CRTES) are in charge of controlling fundamental parts of embedded system, e.g. energy harvesting solar panels in satellites, steering and breaking in cars, or flight management systems in airplanes. To do so, CRTES require strong evidence of correct functional and timing behavior. The former guarantees that the system operates correctly in response of its inputs; the latter ensures that its operations are performed within a predefined time budget. CRTES aim at increasing the number and complexity of functions. Examples include the incorporation of \smarter" Advanced Driver Assistance System (ADAS) functionality in modern cars or advanced collision avoidance systems in Unmanned Aerial Vehicles (UAVs). All these new features, implemented in software, lead to an exponential growth in both performance requirements and software development complexity. Furthermore, there is a strong need to integrate multiple functions into the same computing platform to reduce the number of processing units, mass and space requirements, etc. Overall, there is a clear need to increase the computing power of current CRTES in order to support new sophisticated and complex functionality, and integrate multiple systems into a single platform. The use of multi- and many-core processor architectures is increasingly seen in the CRTES industry as the solution to cope with the performance demand and cost constraints of future CRTES. Many-cores supply higher performance by exploiting the parallelism of applications while providing a better performance per watt as cores are maintained simpler with respect to complex single-core processors. Moreover, the parallelization capabilities allow scheduling multiple functions into the same processor, maximizing the hardware utilization. However, the use of multi- and many-cores in CRTES also brings a number of challenges related to provide evidence about the correct operation of the system, especially in the timing domain. Hence, despite the advantages of many-cores and the fact that they are nowadays a reality in the embedded domain (e.g. Kalray MPPA, Freescale NXP P4080, TI Keystone II), their use in CRTES still requires finding efficient ways of providing reliable evidence about the correct operation of the system. This thesis investigates the use of many-core processors in CRTES as a means to satisfy performance demands of future complex applications while providing the necessary timing guarantees. To do so, this thesis contributes to advance the state-of-the-art towards the exploitation of parallel capabilities of many-cores in CRTES contributing in two different computing domains. From the hardware domain, this thesis proposes new many-core designs that enable deriving reliable and tight timing guarantees. From the software domain, we present efficient scheduling and timing analysis techniques to exploit the parallelization capabilities of many-core architectures and to derive tight and trustworthy Worst-Case Execution Time (WCET) estimates of CRTES.Los sistemas críticos empotrados de tiempo real (en ingles Critical Real-Time Embedded Systems, CRTES) se encargan de controlar partes fundamentales de los sistemas integrados, e.g. obtención de la energía de los paneles solares en satélites, la dirección y frenado en automóviles, o el control de vuelo en aviones. Para hacerlo, CRTES requieren fuerte evidencias del correcto comportamiento funcional y temporal. El primero garantiza que el sistema funciona correctamente en respuesta de sus entradas; el último asegura que sus operaciones se realizan dentro de unos limites temporales establecidos previamente. El objetivo de los CRTES es aumentar el número y la complejidad de las funciones. Algunos ejemplos incluyen los sistemas inteligentes de asistencia a la conducción en automóviles modernos o los sistemas avanzados de prevención de colisiones en vehiculos aereos no tripulados. Todas estas nuevas características, implementadas en software,conducen a un crecimiento exponencial tanto en los requerimientos de rendimiento como en la complejidad de desarrollo de software. Además, existe una gran necesidad de integrar múltiples funciones en una sóla plataforma para así reducir el número de unidades de procesamiento, cumplir con requisitos de peso y espacio, etc. En general, hay una clara necesidad de aumentar la potencia de cómputo de los actuales CRTES para soportar nueva funcionalidades sofisticadas y complejas e integrar múltiples sistemas en una sola plataforma. El uso de arquitecturas multi- y many-core se ve cada vez más en la industria CRTES como la solución para hacer frente a la demanda de mayor rendimiento y las limitaciones de costes de los futuros CRTES. Las arquitecturas many-core proporcionan un mayor rendimiento explotando el paralelismo de aplicaciones al tiempo que proporciona un mejor rendimiento por vatio ya que los cores se mantienen más simples con respecto a complejos procesadores de un solo core. Además, las capacidades de paralelización permiten programar múltiples funciones en el mismo procesador, maximizando la utilización del hardware. Sin embargo, el uso de multi- y many-core en CRTES también acarrea ciertos desafíos relacionados con la aportación de evidencias sobre el correcto funcionamiento del sistema, especialmente en el ámbito temporal. Por eso, a pesar de las ventajas de los procesadores many-core y del hecho de que éstos son una realidad en los sitemas integrados (por ejemplo Kalray MPPA, Freescale NXP P4080, TI Keystone II), su uso en CRTES aún precisa de la búsqueda de métodos eficientes para proveer evidencias fiables sobre el correcto funcionamiento del sistema. Esta tesis ahonda en el uso de procesadores many-core en CRTES como un medio para satisfacer los requisitos de rendimiento de aplicaciones complejas mientras proveen las garantías de tiempo necesarias. Para ello, esta tesis contribuye en el avance del estado del arte hacia la explotación de many-cores en CRTES en dos ámbitos de la computación. En el ámbito del hardware, esta tesis propone nuevos diseños many-core que posibilitan garantías de tiempo fiables y precisas. En el ámbito del software, la tesis presenta técnicas eficientes para la planificación de tareas y el análisis de tiempo para aprovechar las capacidades de paralelización en arquitecturas many-core, y también para derivar estimaciones de peor tiempo de ejecución (Worst-Case Execution Time, WCET) fiables y precisas

Innovative Techniques for Testing and Diagnosing SoCs

We rely upon the continued functioning of many electronic devices for our everyday welfare, usually embedding integrated circuits that are becoming even cheaper and smaller with improved features. Nowadays, microelectronics can integrate a working computer with CPU, memories, and even GPUs on a single die, namely System-On-Chip (SoC). SoCs are also employed on automotive safety-critical applications, but need to be tested thoroughly to comply with reliability standards, in particular the ISO26262 functional safety for road vehicles. The goal of this PhD. thesis is to improve SoC reliability by proposing innovative techniques for testing and diagnosing its internal modules: CPUs, memories, peripherals, and GPUs. The proposed approaches in the sequence appearing in this thesis are described as follows: 1. Embedded Memory Diagnosis: Memories are dense and complex circuits which are susceptible to design and manufacturing errors. Hence, it is important to understand the fault occurrence in the memory array. In practice, the logical and physical array representation differs due to an optimized design which adds enhancements to the device, namely scrambling. This part proposes an accurate memory diagnosis by showing the efforts of a software tool able to analyze test results, unscramble the memory array, map failing syndromes to cell locations, elaborate cumulative analysis, and elaborate a final fault model hypothesis. Several SRAM memory failing syndromes were analyzed as case studies gathered on an industrial automotive 32-bit SoC developed by STMicroelectronics. The tool displayed defects virtually, and results were confirmed by real photos taken from a microscope. 2. Functional Test Pattern Generation: The key for a successful test is the pattern applied to the device. They can be structural or functional; the former usually benefits from embedded test modules targeting manufacturing errors and is only effective before shipping the component to the client. The latter, on the other hand, can be applied during mission minimally impacting on performance but is penalized due to high generation time. However, functional test patterns may benefit for having different goals in functional mission mode. Part III of this PhD thesis proposes three different functional test pattern generation methods for CPU cores embedded in SoCs, targeting different test purposes, described as follows: a. Functional Stress Patterns: Are suitable for optimizing functional stress during I Operational-life Tests and Burn-in Screening for an optimal device reliability characterization b. Functional Power Hungry Patterns: Are suitable for determining functional peak power for strictly limiting the power of structural patterns during manufacturing tests, thus reducing premature device over-kill while delivering high test coverage c. Software-Based Self-Test Patterns: Combines the potentiality of structural patterns with functional ones, allowing its execution periodically during mission. In addition, an external hardware communicating with a devised SBST was proposed. It helps increasing in 3% the fault coverage by testing critical Hardly Functionally Testable Faults not covered by conventional SBST patterns. An automatic functional test pattern generation exploiting an evolutionary algorithm maximizing metrics related to stress, power, and fault coverage was employed in the above-mentioned approaches to quickly generate the desired patterns. The approaches were evaluated on two industrial cases developed by STMicroelectronics; 8051-based and a 32-bit Power Architecture SoCs. Results show that generation time was reduced upto 75% in comparison to older methodologies while increasing significantly the desired metrics. 3. Fault Injection in GPGPU: Fault injection mechanisms in semiconductor devices are suitable for generating structural patterns, testing and activating mitigation techniques, and validating robust hardware and software applications. GPGPUs are known for fast parallel computation used in high performance computing and advanced driver assistance where reliability is the key point. Moreover, GPGPU manufacturers do not provide design description code due to content secrecy. Therefore, commercial fault injectors using the GPGPU model is unfeasible, making radiation tests the only resource available, but are costly. In the last part of this thesis, we propose a software implemented fault injector able to inject bit-flip in memory elements of a real GPGPU. It exploits a software debugger tool and combines the C-CUDA grammar to wisely determine fault spots and apply bit-flip operations in program variables. The goal is to validate robust parallel algorithms by studying fault propagation or activating redundancy mechanisms they possibly embed. The effectiveness of the tool was evaluated on two robust applications: redundant parallel matrix multiplication and floating point Fast Fourier Transform

A Multi-level Approach to Evaluate the Impact of GPU Permanent Faults on CNN's Reliability

Graphics processing units (GPUs) are widely used to accelerate Artificial Intelligence applications, such as those based on Convolutional Neural Networks (CNNs). Since in some domains in which CNNs are heavily employed (e.g., automotive and robotics) the expected lifetime of GPUs is over ten years, it is of paramount importance to study the impact of permanent faults (e.g. due to aging). Crucially, while the impact of transient faults on GPUs running CNNs has been widely studied, an accurate evaluation of the impact of permanent faults is still lacking. Performing this evaluation is challenging due to the complexity of GPU devices and the software implementing a CNN. In this work, we propose a methodology that combines the accuracy of gate-level fault simulation with the speed and flexibility of software fault injection to evaluate the effects of permanent hardware faults affecting a GPU. First, we profile the executed low-level GPU instructions during the CNN inference. Then, using extensive gate-level fault injection campaigns, we provide an accurate analysis of the effects of permanent faults on the internal modules executing the targeted instructions. Finally, we propagate these effects using fast software-based fault injection. The method allows, for the first time, to estimate the percentage of permanent faults leading the CNN to produce wrong results (i.e., changing the result of its work). The method's feasibility, which allows for flexibly trade-off accuracy with the required computational effort, is shown using LeNet running on an Ampere Nvidia GPU as a case study. The method reduces the computational effort for the evaluation by several orders of magnitude with respect to plain gate- and RTL-level faults simulation

Evaluation of STT-MRAM main memory for HPC and real-time systems

It is questionable whether DRAM will continue to scale and will meet the needs of next-generation systems. Therefore, significant effort is invested in research and development of novel memory technologies. One of the candidates for nextgeneration memory is Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM). STT-MRAM is an emerging non-volatile memory with a lot of potential that could be exploited for various requirements of different computing systems. Being a novel technology, STT-MRAM devices are already approaching DRAM in terms of capacity, frequency and device size. Special STT-MRAM features such as intrinsic radiation hardness, non-volatility, zero stand-by power and capability to function in extreme temperatures also make it particularly suitable for aerospace, avionics and automotive applications. Despite of being a conceivable alternative for main memory technology, to this day, academic research of STT-MRAM main memory remains marginal. This is mainly due to the unavailability of publicly available detailed timing parameters of this novel technology, which are required to perform a cycle accurate main memory simulation. Some researchers adopt simplistic memory models to simulate main memory, but such models can introduce significant errors in the analysis of the overall system performance. Therefore, detailed timing parameters are a must-have for any evaluation or architecture exploration study of STT-MRAM main memory. These detailed parameters are not publicly available because STT-MRAM manufacturers are reluctant to release any delicate information on the technology. This thesis demonstrates an approach to perform a cycle accurate simulation of STT-MRAM main memory, being the first to release detailed timing parameters of this technology from academia, essentially enabling researchers to conduct reliable system level simulation of STT-MRAM using widely accepted existing simulation infrastructure. Our results show that, in HPC domain STT-MRAM provide performance comparable to DRAM. Results from the power estimation indicates that STT-MRAM power consumption increases significantly for Activation/Precharge power while Burst power increases moderately and Background power does not deviate much from DRAM. The thesis includes detailed STT-MRAM main memory timing parameters to the main repositories of DramSim2 and Ramulator, two of the most widely used and accepted state-of-the-art main memory simulators. The STT-MRAM timing parameters that has been originated as a part of this thesis, are till date the only reliable and publicly available timing information on this memory technology published from academia. Finally, the thesis analyzes the feasibility of using STT-MRAM in real-time embedded systems by investigating STT-MRAM main memory impact on average system performance and WCET. STT-MRAM's suitability for the real-time embedded systems is validated on benchmarks provided by the European Space Agency (ESA), EEMBC Autobench and MediaBench suite by analyzing performance and WCET impact. In quantitative terms, our results show that STT-MRAM main memory in real-time embedded systems provides performance and WCET comparable to conventional DRAM, while opening up opportunities to exploit various advantages.Es cuestionable si DRAM continuará escalando y cumplirá con las necesidades de los sistemas de la próxima generación. Por lo tanto, se invierte un esfuerzo significativo en la investigación y el desarrollo de nuevas tecnologías de memoria. Uno de los candidatos para la memoria de próxima generación es la Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM). STT-MRAM es una memoria no volátil emergente con un gran potencial que podría ser explotada para diversos requisitos de diferentes sistemas informáticos. Al ser una tecnología novedosa, los dispositivos STT-MRAM ya se están acercando a la DRAM en términos de capacidad, frecuencia y tamaño del dispositivo. Las características especiales de STTMRAM, como la dureza intrínseca a la radiación, la no volatilidad, la potencia de reserva cero y la capacidad de funcionar en temperaturas extremas, también lo hacen especialmente adecuado para aplicaciones aeroespaciales, de aviónica y automotriz. A pesar de ser una alternativa concebible para la tecnología de memoria principal, hasta la fecha, la investigación académica de la memoria principal de STT-MRAM sigue siendo marginal. Esto se debe principalmente a la falta de disponibilidad de los parámetros de tiempo detallados públicamente disponibles de esta nueva tecnología, que se requieren para realizar un ciclo de simulación de memoria principal precisa. Algunos investigadores adoptan modelos de memoria simplistas para simular la memoria principal, pero tales modelos pueden introducir errores significativos en el análisis del rendimiento general del sistema. Por lo tanto, los parámetros de tiempo detallados son indispensables para cualquier evaluación o estudio de exploración de la arquitectura de la memoria principal de STT-MRAM. Estos parámetros detallados no están disponibles públicamente porque los fabricantes de STT-MRAM son reacios a divulgar información delicada sobre la tecnología. Esta tesis demuestra un enfoque para realizar un ciclo de simulación precisa de la memoria principal de STT-MRAM, siendo el primero en lanzar parámetros de tiempo detallados de esta tecnología desde la academia, lo que esencialmente permite a los investigadores realizar una simulación confiable a nivel de sistema de STT-MRAM utilizando una simulación existente ampliamente aceptada infraestructura. Nuestros resultados muestran que, en el dominio HPC, STT-MRAM proporciona un rendimiento comparable al de la DRAM. Los resultados de la estimación de potencia indican que el consumo de potencia de STT-MRAM aumenta significativamente para la activation/Precharge power, mientras que la Burst power aumenta moderadamente y la Background power no se desvía mucho de la DRAM. La tesis incluye parámetros detallados de temporización memoria principal de STT-MRAM a los repositorios principales de DramSim2 y Ramulator, dos de los simuladores de memoria principal más avanzados y más utilizados y aceptados. Los parámetros de tiempo de STT-MRAM que se han originado como parte de esta tesis, son hasta la fecha la única información de tiempo confiable y disponible al público sobre esta tecnología de memoria publicada desde la academia. Finalmente, la tesis analiza la viabilidad de usar STT-MRAM en real-time embedded systems mediante la investigación del impacto de la memoria principal de STT-MRAM en el rendimiento promedio del sistema y WCET. La idoneidad de STTMRAM para los real-time embedded systems se valida en los applicaciones proporcionados por la European Space Agency (ESA), EEMBC Autobench y MediaBench, al analizar el rendimiento y el impacto de WCET. En términos cuantitativos, nuestros resultados muestran que la memoria principal de STT-MRAM en real-time embedded systems proporciona un desempeño WCET comparable al de una memoria DRAM convencional, al tiempo que abre oportunidades para explotar varias ventajas

Using machine learning techniques to evaluate multicore soft error reliability

Virtual platform frameworks have been extended to allow earlier soft error analysis of more realistic multicore systems (i.e., real software stacks, state-of-the-art ISAs). The high observability and simulation performance of underlying frameworks enable to generate and collect more error/failurerelated data, considering complex software stack configurations, in a reasonable time. When dealing with sizeable failure-related data sets obtained from multiple fault campaigns, it is essential to filter out parameters (i.e., features) without a direct relationship with the system soft error analysis. In this regard, this paper proposes the use of supervised and unsupervised machine learning techniques, aiming to eliminate non-relevant information as well as identify the correlation between fault injection results and application and platform characteristics. This novel approach provides engineers with appropriate means that able are able to investigate new and more efficient fault mitigation techniques. The underlying approach is validated with an extensive data set gathered from more than 1.2 million fault injections, comprising several benchmarks, a Linux OS and parallelization libraries (e.g., MPI, OpenMP), as well as through a realistic automotive case study