Performance optimizations for compiler-based error detection

The trend towards smaller transistor technologies and lower operating voltages stresses the hardware and makes transistors more susceptible to transient errors. In future systems, performance and power gains will come at the cost of unreliable areas on the chip. For this reason, there is an increased need for low-overhead highly-reliable error detection methodologies. In the last years, several techniques have been proposed. The majority of them are based on redundancy which can be implemented at several levels (e.g., hardware, instruction, thread, process, etc). In instruction-level error detection approaches, the compiler replicates the instructions of the program and inserts checks wherever they are needed. The checks evaluate code correctness and decide whether or not an error has occurred. This type of error detection is more flexible than the hardware alternatives. It allows the programmer to choose the protected area of the program and it can be applied without any hardware modifications. On the other hand, the replicated instructions and the checks cause a large slowdown making software techniques less appealing. In this thesis, we propose two techniques that aim at reducing the error detection overhead of compiler-based approaches and improving system’s performance without sacrificing the fault-coverage. The first technique, DRIFT, achieves this by decoupling the execution of the code (original and replicated) from the checks. The checks are compare and jump instructions. The latter ones tend to make the code sequential and prohibit the compiler from performing aggressive instruction scheduling optimizations. We call this phenomenon basic-block fragmentation. DRIFT reduces the impact of basic-block fragmentation by breaking the synchronized execute-check-confirm-execute cycle. In this way, DRIFT generates a scheduler-friendly code with more instruction-level parallelism (ILP). As a result, it reduces the performance overhead down to 1.29× (on average) and outperforms the state-of-the-art by up to 29.7% retaining the same fault-coverage. Next, CASTED focuses on reducing the impact of error detection overhead on single-chip scalable architectures that are composed of tightly-coupled cores. The proposed compiler methodology adaptively distributes the error detection overhead to the available resources across multiple cores, fully exploiting the abundant ILP of these architectures. CASTED adapts to a wide range of architecture configurations (issue-width, inter-core communication). The results show that CASTED matches the performance of, and often outperforms, sometimes by as mush as 21.2%, the best fixed state-of-the-art approach while maintaining the same fault coverage

Performance and power optimizations in chip multiprocessors for throughput-aware computation

The so-called "power (or power density) wall" has caused core frequency (and single-thread performance) to slow down, giving rise to the era of multi-core/multi-thread processors. For example, the IBM POWER4 processor, released in 2001, incorporated two single-thread cores into the same chip. In 2010, IBM released the POWER7 processor with eight 4-thread cores in the same chip, for a total capacity of 32 execution contexts. The ever increasing number of cores and threads gives rise to new opportunities and challenges for software and hardware architects. At software level, applications can benefit from the abundant number of execution contexts to boost throughput. But this challenges programmers to create highly-parallel applications and operating systems capable of scheduling them correctly. At hardware level, the increasing core and thread count puts pressure on the memory interface, because memory bandwidth grows at a slower pace ---phenomenon known as the "bandwidth (or memory) wall". In addition to memory bandwidth issues, chip power consumption rises due to manufacturers' difficulty to lower operating voltages sufficiently every processor generation. This thesis presents innovations to improve bandwidth and power consumption in chip multiprocessors (CMPs) for throughput-aware computation: a bandwidth-optimized last-level cache (LLC), a bandwidth-optimized vector register file, and a power/performance-aware thread placement heuristic. In contrast to state-of-the-art LLC designs, our organization avoids data replication and, hence, does not require keeping data coherent. Instead, the address space is statically distributed all over the LLC (in a fine-grained interleaving fashion). The absence of data replication increases the cache effective capacity, which results in better hit rates and higher bandwidth compared to a coherent LLC. We use double buffering to hide the extra access latency due to the lack of data replication. The proposed vector register file is composed of thousands of registers and organized as an aggregation of banks. We leverage such organization to attach small special-function "local computation elements" (LCEs) to each bank. This approach ---referred to as the "processor-in-regfile" (PIR) strategy--- overcomes the limited number of register file ports. Because each LCE is a SIMD computation element and all of them can proceed concurrently, the PIR strategy constitutes a highly-parallel super-wide-SIMD device (ideal for throughput-aware computation). Finally, we present a heuristic to reduce chip power consumption by dynamically placing software (application) threads across hardware (physical) threads. The heuristic gathers chip-level power and performance information at runtime to infer characteristics of the applications being executed. For example, if an application's threads share data, the heuristic may decide to place them in fewer cores to favor inter-thread data sharing and communication. In such case, the number of active cores decreases, which is a good opportunity to switch off the unused cores to save power. It is increasingly harder to find bulletproof (micro-)architectural solutions for the bandwidth and power scalability limitations in CMPs. Consequently, we think that architects should attack those problems from different flanks simultaneously, with complementary innovations. This thesis contributes with a battery of solutions to alleviate those problems in the context of throughput-aware computation: 1) proposing a bandwidth-optimized LLC; 2) proposing a bandwidth-optimized register file organization; and 3) proposing a simple technique to improve power-performance efficiency.El excesivo consumo de potencia de los procesadores actuales ha desacelerado el incremento en la frecuencia operativa de los mismos para dar lugar a la era de los procesadores con múltiples núcleos y múltiples hilos de ejecución. Por ejemplo, el procesador POWER7 de IBM, lanzado al mercado en 2010, incorpora ocho núcleos en el mismo chip, con cuatro hilos de ejecución por núcleo. Esto da lugar a nuevas oportunidades y desafíos para los arquitectos de software y hardware. A nivel de software, las aplicaciones pueden beneficiarse del abundante número de núcleos e hilos de ejecución para aumentar el rendimiento. Pero esto obliga a los programadores a crear aplicaciones altamente paralelas y sistemas operativos capaces de planificar correctamente la ejecución de las mismas. A nivel de hardware, el creciente número de núcleos e hilos de ejecución ejerce presión sobre la interfaz de memoria, ya que el ancho de banda de memoria crece a un ritmo más lento. Además de los problemas de ancho de banda de memoria, el consumo de energía del chip se eleva debido a la dificultad de los fabricantes para reducir suficientemente los voltajes de operación entre generaciones de procesadores. Esta tesis presenta innovaciones para mejorar el ancho de banda y consumo de energía en procesadores multinúcleo en el ámbito de la computación orientada a rendimiento ("throughput-aware computation"): una memoria caché de último nivel ("last-level cache" o LLC) optimizada para ancho de banda, un banco de registros vectorial optimizado para ancho de banda, y una heurística para planificar la ejecución de aplicaciones paralelas orientada a mejorar la eficiencia del consumo de potencia y desempeño. En contraste con los diseños de LLC de última generación, nuestra organización evita la duplicación de datos y, por tanto, no requiere de técnicas de coherencia. El espacio de direcciones de memoria se distribuye estáticamente en la LLC con un entrelazado de grano fino. La ausencia de replicación de datos aumenta la capacidad efectiva de la memoria caché, lo que se traduce en mejores tasas de acierto y mayor ancho de banda en comparación con una LLC coherente. Utilizamos la técnica de "doble buffering" para ocultar la latencia adicional necesaria para acceder a datos remotos. El banco de registros vectorial propuesto se compone de miles de registros y se organiza como una agregación de bancos. Incorporamos a cada banco una pequeña unidad de cómputo de propósito especial ("local computation element" o LCE). Este enfoque ---que llamamos "computación en banco de registros"--- permite superar el número limitado de puertos en el banco de registros. Debido a que cada LCE es una unidad de cómputo con soporte SIMD ("single instruction, multiple data") y todas ellas pueden proceder de forma concurrente, la estrategia de "computación en banco de registros" constituye un dispositivo SIMD altamente paralelo. Por último, presentamos una heurística para planificar la ejecución de aplicaciones paralelas orientada a reducir el consumo de energía del chip, colocando dinámicamente los hilos de ejecución a nivel de software entre los hilos de ejecución a nivel de hardware. La heurística obtiene, en tiempo de ejecución, información de consumo de potencia y desempeño del chip para inferir las características de las aplicaciones. Por ejemplo, si los hilos de ejecución a nivel de software comparten datos significativamente, la heurística puede decidir colocarlos en un menor número de núcleos para favorecer el intercambio de datos entre ellos. En tal caso, los núcleos no utilizados se pueden apagar para ahorrar energía. Cada vez es más difícil encontrar soluciones de arquitectura "a prueba de balas" para resolver las limitaciones de escalabilidad de los procesadores actuales. En consecuencia, creemos que los arquitectos deben atacar dichos problemas desde diferentes flancos simultáneamente, con innovaciones complementarias

Doctor of Philosophy

dissertationWith the explosion of chip transistor counts, the semiconductor industry has struggled with ways to continue scaling computing performance in line with historical trends. In recent years, the de facto solution to utilize excess transistors has been to increase the size of the on-chip data cache, allowing fast access to an increased portion of main memory. These large caches allowed the continued scaling of single thread performance, which had not yet reached the limit of instruction level parallelism (ILP). As we approach the potential limits of parallelism within a single threaded application, new approaches such as chip multiprocessors (CMP) have become popular for scaling performance utilizing thread level parallelism (TLP). This dissertation identifies the operating system as a ubiquitous area where single threaded performance and multithreaded performance have often been ignored by computer architects. We propose that novel hardware and OS co-design has the potential to significantly improve current chip multiprocessor designs, enabling increased performance and improved power efficiency. We show that the operating system contributes a nontrivial overhead to even the most computationally intense workloads and that this OS contribution grows to a significant fraction of total instructions when executing several common applications found in the datacenter. We demonstrate that architectural improvements have had little to no effect on the performance of the OS over the last 15 years, leaving ample room for improvements. We specifically consider three potential solutions to improve OS execution on modern processors. First, we consider the potential of a separate operating system processor (OSP) operating concurrently with general purpose processors (GPP) in a chip multiprocessor organization, with several specialized structures acting as efficient conduits between these processors. Second, we consider the potential of segregating existing caching structures to decrease cache interference between the OS and application. Third, we propose that there are components within the OS itself that should be refactored to be both multithreaded and cache topology aware, which in turn, improves the performance and scalability of many-threaded applications

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

Modern graphics processing units (GPUs) with many-core architectures have emerged as general-purpose parallel computing platforms that can accelerate simulation science applications tremendously. While multi-GPU workstations with several TeraFLOPS of peak computing power are available to accelerate computational problems, larger problems require even more resources. Conventional clusters of central processing units (CPU) are now being augmented with multiple GPUs in each compute-node to tackle large problems. The heterogeneous architecture of a multi-GPU cluster with a deep memory hierarchy creates unique challenges in developing scalable and efficient simulation codes. In this study, we pursue mixed MPI-CUDA implementations and investigate three strategies to probe the efficiency and scalability of incompressible flow computations on the Lincoln Tesla cluster at the National Center for Supercomputing Applications (NCSA). We exploit some of the advanced features of MPI and CUDA programming to overlap both GPU data transfer and MPI communications with computations on the GPU. We sustain approximately 2.4 TeraFLOPS on the 64 nodes of the NCSA Lincoln Tesla cluster using 128 GPUs with a total of 30,720 processing elements. Our results demonstrate that multi-GPU clusters can substantially accelerate computational fluid dynamics (CFD) simulations

An extension to VORO++ for multithreaded computation of Voronoi cells

VORO++ is a software library written in C++ for computing the Voronoi tessellation, a technique in computational geometry that is widely used for analyzing systems of particles. VORO++ was released in 2009 and is based on computing the Voronoi cell for each particle individually. Here, we take advantage of modern computer hardware, and extend the original serial version to allow for multithreaded computation of Voronoi cells via the OpenMP application programming interface. We test the performance of the code, and demonstrate that we can achieve parallel efficiencies greater than 95% in many cases. The multithreaded extension follows standard OpenMP programming paradigms, allowing it to be incorporated into other programs. We provide an example of this using the VoroTop software library, performing a multithreaded Voronoi cell topology analysis of up to 102.4 million particles.Comment: Fix typo and section number

Methods for Robust and Energy-Efficient Microprocessor Architectures

Σήμερα, η εξέλιξη της τεχνολογίας επιτρέπει τη βελτίωση τριών βασικών στοιχείων της σχεδίασης των επεξεργαστών: αυξημένες επιδόσεις, χαμηλότερη κατανάλωση ισχύος και χαμηλότερο κόστος παραγωγής του τσιπ, ενώ οι σχεδιαστές επεξεργαστών έχουν επικεντρωθεί στην παραγωγή επεξεργαστών με περισσότερες λειτουργίες σε χαμηλότερο κόστος. Οι σημερινοί επεξεργαστές είναι πολύ ταχύτεροι και διαθέτουν εξελιγμένες λειτουργικές μονάδες συγκριτικά με τους προκατόχους τους, ωστόσο, καταναλώνουν αρκετά μεγάλη ενέργεια. Τα ποσά ηλεκτρικής ισχύος που καταναλώνονται, και η επακόλουθη έκλυση θερμότητας, αυξάνονται παρά τη μείωση του μεγέθους των τρανζίστορ. Αναπτύσσοντας όλο και πιο εξελιγμένους μηχανισμούς και λειτουργικές μονάδες για την αύξηση της απόδοσης και βελτίωση της ενέργειας, σε συνδυασμό με τη μείωση του μεγέθους των τρανζίστορ, οι επεξεργαστές έχουν γίνει εξαιρετικά πολύπλοκα συστήματα, καθιστώντας τη διαδικασία της επικύρωσής τους σημαντική πρόκληση για τη βιομηχανία ολοκληρωμένων κυκλωμάτων. Συνεπώς, οι κατασκευαστές επεξεργαστών αφιερώνουν επιπλέον χρόνο, προϋπολογισμό και χώρο στο τσιπ για να διασφαλίσουν ότι οι επεξεργαστές θα λειτουργούν σωστά κατά τη διάθεσή τους στη αγορά. Για τους λόγους αυτούς, η εργασία αυτή παρουσιάζει νέες μεθόδους για την επιτάχυνση και τη βελτίωση της φάσης της επικύρωσης, καθώς και για τη βελτίωση της ενεργειακής απόδοσης των σύγχρονων επεξεργαστών. Στο πρώτο μέρος της διατριβής προτείνονται δύο διαφορετικές μέθοδοι για την επικύρωση του επεξεργαστή, οι οποίες συμβάλλουν στην επιτάχυνση αυτής της διαδικασίας και στην αποκάλυψη σπάνιων σφαλμάτων στους μηχανισμούς μετάφρασης διευθύνσεων των σύγχρονων επεξεργαστών. Και οι δύο μέθοδοι καθιστούν ευκολότερη την ανίχνευση και τη διάγνωση σφαλμάτων, και επιταχύνουν την ανίχνευση του σφάλματος κατά τη φάση της επικύρωσης. Στο δεύτερο μέρος της διατριβής παρουσιάζεται μια λεπτομερής μελέτη χαρακτηρισμού των περιθωρίων τάσης σε επίπεδο συστήματος σε δύο σύγχρονους ARMv8 επεξεργαστές. Η μελέτη του χαρακτηρισμού προσδιορίζει τα αυξημένα περιθώρια τάσης που έχουν προκαθοριστεί κατά τη διάρκεια κατασκευής του κάθε μεμονωμένου πυρήνα του επεξεργαστή και αναλύει τυχόν απρόβλεπτες συμπεριφορές που μπορεί να προκύψουν σε συνθήκες μειωμένης τάσης. Για την μελέτη και καταγραφή της συμπεριφοράς του συστήματος υπό συνθήκες μειωμένης τάσης, παρουσιάζεται επίσης σε αυτή τη διατριβή μια απλή και ενοποιημένη συνάρτηση: η συνάρτηση πυκνότητας-σοβαρότητας. Στη συνέχεια, παρουσιάζεται αναλυτικά η ανάπτυξη ειδικά σχεδιασμένων προγραμμάτων (micro-viruses) τα οποία υποβάλουν της θεμελιώδεις δομές του επεξεργαστή σε μεγάλο φορτίο εργασίας. Αυτά τα προγράμματα στοχεύουν στην γρήγορη αναγνώριση των ασφαλών περιθωρίων τάσης. Τέλος, πραγματοποιείται ο χαρακτηρισμός των περιθωρίων τάσης σε εκτελέσεις πολλαπλών πυρήνων, καθώς επίσης και σε διαφορετικές συχνότητες, και προτείνεται ένα πρόγραμμα το οποίο εκμεταλλεύεται όλες τις διαφορετικές πτυχές του προβλήματος της κατανάλωσης ενέργειας και παρέχει μεγάλη εξοικονόμηση ενέργειας διατηρώντας παράλληλα υψηλά επίπεδα απόδοσης. Αυτή η μελέτη έχει ως στόχο τον εντοπισμό και την ανάλυση της σχέσης μεταξύ ενέργειας και απόδοσης σε διαφορετικούς συνδυασμούς τάσης και συχνότητας, καθώς και σε διαφορετικό αριθμό νημάτων/διεργασιών που εκτελούνται στο σύστημα, αλλά και κατανομής των προγραμμάτων στους διαθέσιμους πυρήνες.Technology scaling has enabled improvements in the three major design optimization objectives: increased performance, lower power consumption, and lower die cost, while system design has focused on bringing more functionality into products at lower cost. While today's microprocessors, are much faster and much more versatile than their predecessors, they also consume much power. As operating frequency and integration density increase, the total chip power dissipation increases. This is evident from the fact that due to the demand for increased functionality on a single chip, more and more transistors are being packed on a single die and hence, the switching frequency increases in every technology generation. However, by developing aggressive and sophisticated mechanisms to boost performance and to enhance the energy efficiency in conjunction with the decrease of the size of transistors, microprocessors have become extremely complex systems, making the microprocessor verification and manufacturing testing a major challenge for the semiconductor industry. Manufacturers, therefore, choose to spend extra effort, time, budget and chip area to ensure that the delivered products are operating correctly. To meet high-dependability requirements, manufacturers apply a sequence of verification tasks throughout the entire life-cycle of the microprocessor to ensure the correct functionality of the microprocessor chips from the various types of errors that may occur after the products are released to the market. To this end, this work presents novel methods for ensuring the correctness of the microprocessor during the post-silicon validation phase and for improving the energy efficiency requirements of modern microprocessors. These methods can be applied during the prototyping phase of the microprocessors or after their release to the market. More specifically, in the first part of the thesis, we present and describe two different ISA-independent software-based post-silicon validation methods, which contribute to formalization and modeling as well as the acceleration of the post-silicon validation process and expose difficult-to-find bugs in the address translation mechanisms (ATM) of modern microprocessors. Both methods improve the detection and diagnosis of a hardware design bug in the ATM structures and significantly accelerate the bug detection during the post-silicon validation phase. In the second part of the thesis we present a detailed system-level voltage scaling characterization study for two state-of-the-art ARMv8-based multicore CPUs. We present an extensive characterization study which identifies the pessimistic voltage guardbands (the increased voltage margins set by the manufacturer) of each individual microprocessor core and analyze any abnormal behavior that may occur in off-nominal voltage conditions. Towards the formalization of the any abnormal behavior we also present a simple consolidated function; the Severity function, which aggregates the effects of reduced voltage operation. We then introduce the development of dedicated programs (diagnostic micro-viruses) that aim to accelerate the time-consuming voltage margins characterization studies by stressing the fundamental hardware components. Finally, we present a comprehensive exploration of how two server-grade systems behave in different frequency and core allocation configurations beyond nominal voltage operation in multicore executions. This analysis aims (1) to identify the best performance per watt operation points, (2) to reveal how and why the different core allocation options affect the energy consumption, and (3) to enhance the default Linux scheduler to take task allocation decisions for balanced performance and energy efficiency

Applications in GNSS water vapor tomography

Algebraic reconstruction algorithms are iterative algorithms that are used in many area including medicine, seismology or meteorology. These algorithms are known to be highly computational intensive. This may be especially troublesome for real-time applications or when processed by conventional low-cost personnel computers. One of these real time applications is the reconstruction of water vapor images from Global Navigation Satellite System (GNSS) observations. The parallelization of algebraic reconstruction algorithms has the potential to diminish signi cantly the required resources permitting to obtain valid solutions in time to be used for nowcasting and forecasting weather models. The main objective of this dissertation was to present and analyse diverse shared memory libraries and techniques in CPU and GPU for algebraic reconstruction algorithms. It was concluded that the parallelization compensates over sequential implementations. Overall the GPU implementations were found to be only slightly faster than the CPU implementations, depending on the size of the problem being studied. A secondary objective was to develop a software to perform the GNSS water vapor reconstruction using the implemented parallel algorithms. This software has been developed with success and diverse tests were made namely with synthetic and real data, the preliminary results shown to be satisfactory. This dissertation was written in the Space & Earth Geodetic Analysis Laboratory (SEGAL) and was carried out in the framework of the Structure of Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC/CTE-ATM/119922/2010) project funded by FCT.Algoritmos de reconstrução algébrica são algoritmos iterativos que são usados em muitas áreas incluindo medicina, sismologia ou meteorologia. Estes algoritmos são conhecidos por serem bastante exigentes computacionalmente. Isto pode ser especialmente complicado para aplicações de tempo real ou quando processados por computadores pessoais de baixo custo. Uma destas aplicações de tempo real é a reconstrução de imagens de vapor de água a partir de observações de sistemas globais de navegação por satélite. A paralelização dos algoritmos de reconstrução algébrica permite que se reduza significativamente os requisitos computacionais permitindo obter soluções válidas para previsão meteorológica num curto espaço de tempo. O principal objectivo desta dissertação é apresentar e analisar diversas bibliotecas e técnicas multithreading para a reconstrução algébrica em CPU e GPU. Foi concluído que a paralelização compensa sobre a implementações sequenciais. De um modo geral as implementações GPU obtiveram resultados relativamente melhores que implementações em CPU, isto dependendo do tamanho do problema a ser estudado. Um objectivo secundário era desenvolver uma aplicação que realizasse a reconstrução de imagem de vapor de água através de sistemas globais de navegação por satélite de uma forma paralela. Este software tem sido desenvolvido com sucesso e diversos testes foram realizados com dados sintéticos e dados reais, os resultados preliminares foram satisfatórios. Esta dissertação foi escrita no Space & Earth Geodetic Analysis Laboratory (SEGAL) e foi realizada de acordo com o projecto Structure 01' Moist convection in high-resolution GNSS observations and models (SMOG) (PTDC / CTE-ATM/ 11992212010) financiado pelo FCT.Fundação para a Ciência e a Tecnologia (FCT