Automated Debugging Methodology for FPGA-based Systems

Electronic devices make up a vital part of our lives. These are seen from mobiles, laptops, computers, home automation, etc. to name a few. The modern designs constitute billions of transistors. However, with this evolution, ensuring that the devices fulfill the designer’s expectation under variable conditions has also become a great challenge. This requires a lot of design time and effort. Whenever an error is encountered, the process is re-started. Hence, it is desired to minimize the number of spins required to achieve an error-free product, as each spin results in loss of time and effort. Software-based simulation systems present the main technique to ensure the verification of the design before fabrication. However, few design errors (bugs) are likely to escape the simulation process. Such bugs subsequently appear during the post-silicon phase. Finding such bugs is time-consuming due to inherent invisibility of the hardware. Instead of software simulation of the design in the pre-silicon phase, post-silicon techniques permit the designers to verify the functionality through the physical implementations of the design. The main benefit of the methodology is that the implemented design in the post-silicon phase runs many order-of-magnitude faster than its counterpart in pre-silicon. This allows the designers to validate their design more exhaustively. This thesis presents five main contributions to enable a fast and automated debugging solution for reconfigurable hardware. During the research work, we used an obstacle avoidance system for robotic vehicles as a use case to illustrate how to apply the proposed debugging solution in practical environments. The first contribution presents a debugging system capable of providing a lossless trace of debugging data which permits a cycle-accurate replay. This methodology ensures capturing permanent as well as intermittent errors in the implemented design. The contribution also describes a solution to enhance hardware observability. It is proposed to utilize processor-configurable concentration networks, employ debug data compression to transmit the data more efficiently, and partially reconfiguring the debugging system at run-time to save the time required for design re-compilation as well as preserve the timing closure. The second contribution presents a solution for communication-centric designs. Furthermore, solutions for designs with multi-clock domains are also discussed. The third contribution presents a priority-based signal selection methodology to identify the signals which can be more helpful during the debugging process. A connectivity generation tool is also presented which can map the identified signals to the debugging system. The fourth contribution presents an automated error detection solution which can help in capturing the permanent as well as intermittent errors without continuous monitoring of debugging data. The proposed solution works for designs even in the absence of golden reference. The fifth contribution proposes to use artificial intelligence for post-silicon debugging. We presented a novel idea of using a recurrent neural network for debugging when a golden reference is present for training the network. Furthermore, the idea was also extended to designs where golden reference is not present

FASTER: Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration

The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) EU FP7 project, aims to ease the design and implementation of dynamically changing hardware systems. Our motivation stems from the promise reconfigurable systems hold for achieving high performance and extending product functionality and lifetime via the addition of new features that operate at hardware speed. However, designing a changing hardware system is both challenging and time-consuming. FASTER facilitates the use of reconfigurable technology by providing a complete methodology enabling designers to easily specify, analyze, implement and verify applications on platforms with general-purpose processors and acceleration modules implemented in the latest reconfigurable technology. Our tool-chain supports both coarse- and fine-grain FPGA reconfiguration, while during execution a flexible run-time system manages the reconfigurable resources. We target three applications from different domains. We explore the way each application benefits from reconfiguration, and then we asses them and the FASTER tools, in terms of performance, area consumption and accuracy of analysis

Re-use of tests and arguments for assesing dependable mixed-critically systems

The safety assessment of mixed-criticality systems (MCS) is a challenging activity due to system heterogeneity, design constraints and increasing complexity. The foundation for MCSs is the integrated architecture paradigm, where a compact hardware comprises multiple execution platforms and communication interfaces to implement concurrent functions with different safety requirements. Besides a computing platform providing adequate isolation and fault tolerance mechanism, the development of an MCS application shall also comply with the guidelines defined by the safety standards. A way to lower the overall MCS certification cost is to adopt a platform-based design (PBD) development approach. PBD is a model-based development (MBD) approach, where separate models of logic, hardware and deployment support the analysis of the resulting system properties and behaviour. The PBD development of MCSs benefits from a composition of modular safety properties (e.g. modular safety cases), which support the derivation of mixed-criticality product lines. The validation and verification (V&V) activities claim a substantial effort during the development of programmable electronics for safety-critical applications. As for the MCS dependability assessment, the purpose of the V&V is to provide evidences supporting the safety claims. The model-based development of MCSs adds more V&V tasks, because additional analysis (e.g., simulations) need to be carried out during the design phase. During the MCS integration phase, typically hardware-in-the-loop (HiL) plant simulators support the V&V campaigns, where test automation and fault-injection are the key to test repeatability and thorough exercise of the safety mechanisms. This dissertation proposes several V&V artefacts re-use strategies to perform an early verification at system level for a distributed MCS, artefacts that later would be reused up to the final stages in the development process: a test code re-use to verify the fault-tolerance mechanisms on a functional model of the system combined with a non-intrusive software fault-injection, a model to X-in-the-loop (XiL) and code-to-XiL re-use to provide models of the plant and distributed embedded nodes suited to the HiL simulator, and finally, an argumentation framework to support the automated composition and staged completion of modular safety-cases for dependability assessment, in the context of the platform-based development of mixed-criticality systems relying on the DREAMS harmonized platform.La dificultad para evaluar la seguridad de los sistemas de criticidad mixta (SCM) aumenta con la heterogeneidad del sistema, las restricciones de diseño y una complejidad creciente. Los SCM adoptan el paradigma de arquitectura integrada, donde un hardware embebido compacto comprende múltiples plataformas de ejecución e interfaces de comunicación para implementar funciones concurrentes y con diferentes requisitos de seguridad. Además de una plataforma de computación que provea un aislamiento y mecanismos de tolerancia a fallos adecuados, el desarrollo de una aplicación SCM además debe cumplir con las directrices definidas por las normas de seguridad. Una forma de reducir el coste global de la certificación de un SCM es adoptar un enfoque de desarrollo basado en plataforma (DBP). DBP es un enfoque de desarrollo basado en modelos (DBM), en el que modelos separados de lógica, hardware y despliegue soportan el análisis de las propiedades y el comportamiento emergente del sistema diseñado. El desarrollo DBP de SCMs se beneficia de una composición modular de propiedades de seguridad (por ejemplo, casos de seguridad modulares), que facilitan la definición de líneas de productos de criticidad mixta. Las actividades de verificación y validación (V&V) representan un esfuerzo sustancial durante el desarrollo de aplicaciones basadas en electrónica confiable. En la evaluación de la seguridad de un SCM el propósito de las actividades de V&V es obtener las evidencias que apoyen las aseveraciones de seguridad. El desarrollo basado en modelos de un SCM incrementa las tareas de V&V, porque permite realizar análisis adicionales (por ejemplo, simulaciones) durante la fase de diseño. En las campañas de pruebas de integración de un SCM habitualmente se emplean simuladores de planta hardware-in-the-loop (HiL), en donde la automatización de pruebas y la inyección de faltas son la clave para la repetitividad de las pruebas y para ejercitar completamente los mecanismos de tolerancia a fallos. Esta tesis propone diversas estrategias de reutilización de artefactos de V&V para la verificación temprana de un MCS distribuido, artefactos que se emplearán en ulteriores fases del desarrollo: la reutilización de código de prueba para verificar los mecanismos de tolerancia a fallos sobre un modelo funcional del sistema combinado con una inyección de fallos de software no intrusiva, la reutilización de modelo a X-in-the-loop (XiL) y código a XiL para obtener modelos de planta y nodos distribuidos aptos para el simulador HiL y, finalmente, un marco de argumentación para la composición automatizada y la compleción escalonada de casos de seguridad modulares, en el contexto del desarrollo basado en plataformas de sistemas de criticidad mixta empleando la plataforma armonizada DREAMS.Kritikotasun nahastuko sistemen segurtasun ebaluazioa jarduera neketsua da beraien heterogeneotasuna dela eta. Sistema hauen oinarria arkitektura integratuen paradigman datza, non hardware konpaktu batek exekuzio plataforma eta komunikazio interfaze ugari integratu ahal dituen segurtasun baldintza desberdineko funtzio konkurrenteak inplementatzeko. Konputazio plataformek isolamendu eta akatsen aurkako mekanismo egokiak emateaz gain, segurtasun arauek definituriko jarraibideak jarraitu behar dituzte kritikotasun mistodun aplikazioen garapenean. Sistema hauen zertifikazio prozesuaren kostua murrizteko aukera bat plataformetan oinarritutako garapenean (PBD) datza. Garapen planteamendu hau modeloetan oinarrituriko garapena da (MBD) non modeloaren logika, hardware eta garapen desberdinak sistemaren propietateen eta portaeraren aurka aztertzen diren. Kritikotasun mistodun sistemen PBD garapenak etekina ateratzen dio moduluetan oinarrituriko segurtasun propietateei, adibidez: segurtasun kasu modularrak (MSC). Modulu hauek kritikotasun mistodun produktu-lerroak ere hartzen dituzte kontutan. Berifikazio eta balioztatze (V&V) jarduerek esfortzu kontsideragarria eskatzen dute segurtasun-kiritikoetarako elektronika programagarrien garapenean. Kritikotasun mistodun sistemen konfiantzaren ebaluazioaren eta V&V jardueren helburua segurtasun eskariak jasotzen dituzten frogak proportzionatzea da. Kritikotasun mistodun sistemen modelo bidezko garapenek zeregin gehigarriak atxikitzen dizkio V&V jarduerari, fase honetan analisi gehigarriak (hots, simulazioak) zehazten direlako. Bestalde, kritikotasun mistodun sistemen integrazio fasean, hardware-in-the-loop (Hil) simulazio plantek V&V iniziatibak sostengatzen dituzte non testen automatizazioan eta akatsen txertaketan funtsezko jarduerak diren. Jarduera hauek frogen errepikapena eta segurtasun mekanismoak egiaztzea ahalbidetzen dute. Tesi honek V&V artefaktuen berrerabilpenerako estrategiak proposatzen ditu, kritikotasun mistodun sistemen egiaztatze azkarrerako sistema mailan eta garapen prozesuko azken faseetaraino erabili daitezkeenak. Esate baterako, test kodearen berrabilpena akats aurkako mekanismoak egiaztatzeko, modelotik X-in-the-loop (XiL)-ra eta kodetik XiL-rako konbertsioa HiL simulaziorako eta argumentazio egitura bat DREAMS Europear proiektuan definituriko arkitektura estiloan oinarrituriko segurtasun kasu modularrak automatikoki eta gradualki sortzeko

Novel Architectures for Offloading and Accelerating Computations in Artificial Intelligence and Big Data

Due to the end of Moore's Law and Dennard Scaling, performance gains in general-purpose architectures have significantly slowed in recent years. While raising the number of cores has been a viable approach for further performance increases, Amdahl's Law and its implications on parallelization also limit further performance gains. Consequently, research has shifted towards different approaches, including domain-specific custom architectures tailored to specific workloads. This has led to a new golden age for computer architecture, as noted in the Turing Award Lecture by Hennessy and Patterson, which has spawned several new architectures and architectural advances specifically targeted at highly current workloads, including Machine Learning. This thesis introduces a hierarchy of architectural improvements ranging from minor incremental changes, such as High-Bandwidth Memory, to more complex architectural extensions that offload workloads from the general-purpose CPU towards more specialized accelerators. Finally, we introduce novel architectural paradigms, namely Near-Data or In-Network Processing, as the most complex architectural improvements. This cumulative dissertation then investigates several architectural improvements to accelerate Sum-Product Networks, a novel Machine Learning approach from the class of Probabilistic Graphical Models. Furthermore, we use these improvements as case studies to discuss the impact of novel architectures, showing that minor and major architectural changes can significantly increase performance in Machine Learning applications. In addition, this thesis presents recent works on Near-Data Processing, which introduces Smart Storage Devices as a novel architectural paradigm that is especially interesting in the context of Big Data. We discuss how Near-Data Processing can be applied to improve performance in different database settings by offloading database operations to smart storage devices. Offloading data-reductive operations, such as selections, reduces the amount of data transferred, thus improving performance and alleviating bandwidth-related bottlenecks. Using Near-Data Processing as a use-case, we also discuss how Machine Learning approaches, like Sum-Product Networks, can improve novel architectures. Specifically, we introduce an approach for offloading Cardinality Estimation using Sum-Product Networks that could enable more intelligent decision-making in smart storage devices. Overall, we show that Machine Learning can benefit from developing novel architectures while also showing that Machine Learning can be applied to improve the applications of novel architectures

Cross-Layer Rapid Prototyping and Synthesis of Application-Specific and Reconfigurable Many-accelerator Platforms

Technological advances of recent years laid the foundation consolidation of informatisationof society, impacting on economic, political, cultural and socialdimensions. At the peak of this realization, today, more and more everydaydevices are connected to the web, giving the term ”Internet of Things”. The futureholds the full connection and interaction of IT and communications systemsto the natural world, delimiting the transition to natural cyber systems and offeringmeta-services in the physical world, such as personalized medical care, autonomoustransportation, smart energy cities etc. . Outlining the necessities of this dynamicallyevolving market, computer engineers are required to implement computingplatforms that incorporate both increased systemic complexity and also cover awide range of meta-characteristics, such as the cost and design time, reliabilityand reuse, which are prescribed by a conflicting set of functional, technical andconstruction constraints. This thesis aims to address these design challenges bydeveloping methodologies and hardware/software co-design tools that enable therapid implementation and efficient synthesis of architectural solutions, which specifyoperating meta-features required by the modern market. Specifically, this thesispresents a) methodologies to accelerate the design flow for both reconfigurableand application-specific architectures, b) coarse-grain heterogeneous architecturaltemplates for processing and communication acceleration and c) efficient multiobjectivesynthesis techniques both at high abstraction level of programming andphysical silicon level.Regarding to the acceleration of the design flow, the proposed methodologyemploys virtual platforms in order to hide architectural details and drastically reducesimulation time. An extension of this framework introduces the systemicco-simulation using reconfigurable acceleration platforms as co-emulation intermediateplatforms. Thus, the development cycle of a hardware/software productis accelerated by moving from a vertical serial flow to a circular interactive loop.Moreover the simulation capabilities are enriched with efficient detection and correctiontechniques of design errors, as well as control methods of performancemetrics of the system according to the desired specifications, during all phasesof the system development. In orthogonal correlation with the aforementionedmethodological framework, a new architectural template is proposed, aiming atbridging the gap between design complexity and technological productivity usingspecialized hardware accelerators in heterogeneous systems-on-chip and networkon-chip platforms. It is presented a novel co-design methodology for the hardwareaccelerators and their respective programming software, including the tasks allocationto the available resources of the system/network. The introduced frameworkprovides implementation techniques for the accelerators, using either conventionalprogramming flows with hardware description language or abstract programmingmodel flows, using techniques from high-level synthesis. In any case, it is providedthe option of systemic measures optimization, such as the processing speed,the throughput, the reliability, the power consumption and the design silicon area.Finally, on addressing the increased complexity in design tools of reconfigurablesystems, there are proposed novel multi-objective optimization evolutionary algo-rithms which exploit the modern multicore processors and the coarse-grain natureof multithreaded programming environments (e.g. OpenMP) in order to reduce theplacement time, while by simultaneously grouping the applications based on theirintrinsic characteristics, the effectively explore the design space effectively.The efficiency of the proposed architectural templates, design tools and methodologyflows is evaluated in relation to the existing edge solutions with applicationsfrom typical computing domains, such as digital signal processing, multimedia andarithmetic complexity, as well as from systemic heterogeneous environments, suchas a computer vision system for autonomous robotic space navigation and manyacceleratorsystems for HPC and workstations/datacenters. The results strengthenthe belief of the author, that this thesis provides competitive expertise to addresscomplex modern - and projected future - design challenges.Οι τεχνολογικές εξελίξεις των τελευταίων ετών έθεσαν τα θεμέλια εδραίωσης της πληροφοριοποίησης της κοινωνίας, επιδρώντας σε οικονομικές,πολιτικές, πολιτιστικές και κοινωνικές διαστάσεις. Στο απόγειο αυτής τη ςπραγμάτωσης, σήμερα, ολοένα και περισσότερες καθημερινές συσκευές συνδέονται στο παγκόσμιο ιστό, αποδίδοντας τον όρο «Ίντερνετ των πραγμάτων».Το μέλλον επιφυλάσσει την πλήρη σύνδεση και αλληλεπίδραση των συστημάτων πληροφορικής και επικοινωνιών με τον φυσικό κόσμο, οριοθετώντας τη μετάβαση στα συστήματα φυσικού κυβερνοχώρου και προσφέροντας μεταυπηρεσίες στον φυσικό κόσμο όπως προσωποποιημένη ιατρική περίθαλψη, αυτόνομες μετακινήσεις, έξυπνες ενεργειακά πόλεις κ.α. . Σκιαγραφώντας τις ανάγκες αυτής της δυναμικά εξελισσόμενης αγοράς, οι μηχανικοί υπολογιστών καλούνται να υλοποιήσουν υπολογιστικές πλατφόρμες που αφενός ενσωματώνουν αυξημένη συστημική πολυπλοκότητα και αφετέρου καλύπτουν ένα ευρύ φάσμα μεταχαρακτηριστικών, όπως λ.χ. το κόστος σχεδιασμού, ο χρόνος σχεδιασμού, η αξιοπιστία και η επαναχρησιμοποίηση, τα οποία προδιαγράφονται από ένα αντικρουόμενο σύνολο λειτουργικών, τεχνολογικών και κατασκευαστικών περιορισμών. Η παρούσα διατριβή στοχεύει στην αντιμετώπιση των παραπάνω σχεδιαστικών προκλήσεων, μέσω της ανάπτυξης μεθοδολογιών και εργαλείων συνσχεδίασης υλικού/λογισμικού που επιτρέπουν την ταχεία υλοποίηση καθώς και την αποδοτική σύνθεση αρχιτεκτονικών λύσεων, οι οποίες προδιαγράφουν τα μετα-χαρακτηριστικά λειτουργίας που απαιτεί η σύγχρονη αγορά. Συγκεκριμένα, στα πλαίσια αυτής της διατριβής, παρουσιάζονται α) μεθοδολογίες επιτάχυνσης της ροής σχεδιασμού τόσο για επαναδιαμορφούμενες όσο και για εξειδικευμένες αρχιτεκτονικές, β) ετερογενή αδρομερή αρχιτεκτονικά πρότυπα επιτάχυνσης επεξεργασίας και επικοινωνίας και γ) αποδοτικές τεχνικές πολυκριτηριακής σύνθεσης τόσο σε υψηλό αφαιρετικό επίπεδο προγραμματισμού,όσο και σε φυσικό επίπεδο πυριτίου.Αναφορικά προς την επιτάχυνση της ροής σχεδιασμού, προτείνεται μια μεθοδολογία που χρησιμοποιεί εικονικές πλατφόρμες, οι οποίες αφαιρώντας τις αρχιτεκτονικές λεπτομέρειες καταφέρνουν να μειώσουν σημαντικά το χρόνο εξομοίωσης. Παράλληλα, εισηγείται η συστημική συν-εξομοίωση με τη χρήση επαναδιαμορφούμενων πλατφορμών, ως μέσων επιτάχυνσης. Με αυτόν τον τρόπο, ο κύκλος ανάπτυξης ενός προϊόντος υλικού, μετατεθειμένος από την κάθετη σειριακή ροή σε έναν κυκλικό αλληλεπιδραστικό βρόγχο, καθίσταται ταχύτερος, ενώ οι δυνατότητες προσομοίωσης εμπλουτίζονται με αποδοτικότερες μεθόδους εντοπισμού και διόρθωσης σχεδιαστικών σφαλμάτων, καθώς και μεθόδους ελέγχου των μετρικών απόδοσης του συστήματος σε σχέση με τις επιθυμητές προδιαγραφές, σε όλες τις φάσεις ανάπτυξης του συστήματος. Σε ορθογώνια συνάφεια με το προαναφερθέν μεθοδολογικό πλαίσιο, προτείνονται νέα αρχιτεκτονικά πρότυπα που στοχεύουν στη γεφύρωση του χάσματος μεταξύ της σχεδιαστικής πολυπλοκότητας και της τεχνολογικής παραγωγικότητας, με τη χρήση συστημάτων εξειδικευμένων επιταχυντών υλικού σε ετερογενή συστήματα-σε-ψηφίδα καθώς και δίκτυα-σε-ψηφίδα. Παρουσιάζεται κατάλληλη μεθοδολογία συν-σχεδίασης των επιταχυντών υλικού και του λογισμικού προκειμένου να αποφασισθεί η κατανομή των εργασιών στους διαθέσιμους πόρους του συστήματος/δικτύου. Το μεθοδολογικό πλαίσιο προβλέπει την υλοποίηση των επιταχυντών είτε με συμβατικές μεθόδους προγραμματισμού σε γλώσσα περιγραφής υλικού είτε με αφαιρετικό προγραμματιστικό μοντέλο με τη χρήση τεχνικών υψηλού επιπέδου σύνθεσης. Σε κάθε περίπτωση, δίδεται η δυνατότητα στο σχεδιαστή για βελτιστοποίηση συστημικών μετρικών, όπως η ταχύτητα επεξεργασίας, η ρυθμαπόδοση, η αξιοπιστία, η κατανάλωση ενέργειας και η επιφάνεια πυριτίου του σχεδιασμού. Τέλος, προκειμένου να αντιμετωπισθεί η αυξημένη πολυπλοκότητα στα σχεδιαστικά εργαλεία επαναδιαμορφούμενων συστημάτων, προτείνονται νέοι εξελικτικοί αλγόριθμοι πολυκριτηριακής βελτιστοποίησης, οι οποίοι εκμεταλλευόμενοι τους σύγχρονους πολυπύρηνους επεξεργαστές και την αδρομερή φύση των πολυνηματικών περιβαλλόντων προγραμματισμού (π.χ. OpenMP), μειώνουν το χρόνο επίλυσης του προβλήματος της τοποθέτησης των λογικών πόρων σε φυσικούς,ενώ ταυτόχρονα, ομαδοποιώντας τις εφαρμογές βάση των εγγενών χαρακτηριστικών τους, διερευνούν αποτελεσματικότερα το χώρο σχεδίασης.Η αποδοτικότητά των προτεινόμενων αρχιτεκτονικών προτύπων και μεθοδολογιών επαληθεύτηκε σε σχέση με τις υφιστάμενες λύσεις αιχμής τόσο σε αυτοτελής εφαρμογές, όπως η ψηφιακή επεξεργασία σήματος, τα πολυμέσα και τα προβλήματα αριθμητικής πολυπλοκότητας, καθώς και σε συστημικά ετερογενή περιβάλλοντα, όπως ένα σύστημα όρασης υπολογιστών για αυτόνομα διαστημικά ρομποτικά οχήματα και ένα σύστημα πολλαπλών επιταχυντών υλικού για σταθμούς εργασίας και κέντρα δεδομένων, στοχεύοντας εφαρμογές υψηλής υπολογιστικής απόδοσης (HPC). Τα αποτελέσματα ενισχύουν την πεποίθηση του γράφοντα, ότι η παρούσα διατριβή παρέχει ανταγωνιστική τεχνογνωσία για την αντιμετώπιση των πολύπλοκων σύγχρονων και προβλεπόμενα μελλοντικών σχεδιαστικών προκλήσεων

One size does not fit all : accelerating OLAP workloads with GPUs

GPU has been considered as one of the next-generation platforms for real-time query processing databases. In this paper we empirically demonstrate that the representative GPU databases [e.g., OmniSci (Open Source Analytical Database & SQL Engine,, 2019)] may be slower than the representative in-memory databases [e.g., Hyper (Neumann and Leis, IEEE Data Eng Bull 37(1):3-11, 2014)] with typical OLAP workloads (with Star Schema Benchmark) even if the actual dataset size of each query can completely fit in GPU memory. Therefore, we argue that GPU database designs should not be one-size-fits-all; a general-purpose GPU database engine may not be well-suited for OLAP workloads without careful designed GPU memory assignment and GPU computing locality. In order to achieve better performance for GPU OLAP, we need to re-organize OLAP operators and re-optimize OLAP model. In particular, we propose the 3-layer OLAP model to match the heterogeneous computing platforms. The core idea is to maximize data and computing locality to specified hardware. We design the vector grouping algorithm for data-intensive workload which is proved to be assigned to CPU platform adaptive. We design the TOP-DOWN query plan tree strategy to guarantee the optimal operation in final stage and pushing the respective optimizations to the lower layers to make global optimization gains. With this strategy, we design the 3-stage processing model (OLAP acceleration engine) for hybrid CPU-GPU platform, where the computing-intensive star-join stage is accelerated by GPU, and the data-intensive grouping & aggregation stage is accelerated by CPU. This design maximizes the locality of different workloads and simplifies the GPU acceleration implementation. Our experimental results show that with vector grouping and GPU accelerated star-join implementation, the OLAP acceleration engine runs 1.9x, 3.05x and 3.92x faster than Hyper, OmniSci GPU and OmniSci CPU in SSB evaluation with dataset of SF = 100.Peer reviewe

Linqits: Big data on little clients

ABSTRACT We present LINQits, a flexible hardware template that can be mapped onto programmable logic or ASICs in a heterogeneous system-on-chip for a mobile device or server. Unlike fixed-function accelerators, LINQits accelerates a domainspecific query language called LINQ. LINQits does not provide coverage for all possible applications-however, existing applications (re-)written with LINQ in mind benefit extensively from hardware acceleration. Furthermore, the LINQits framework offers a graceful and transparent migration path from software to hardware. LINQits is prototyped on a 2W heterogeneous SoC called the ZYNQ processor, which combines dual ARM A9 processors with an FPGA on a single die in 28nm silicon technology. Our physical measurements show that LINQits improves energy efficiency by 8.9 to 30.6 times and performance by 10.7 to 38.1 times compared to optimized, multithreaded C programs running on conventional ARM A9 processors

Reconfigurable Computing Systems for Robotics using a Component-Oriented Approach

Robotic platforms are becoming more complex due to the wide range of modern applications, including multiple heterogeneous sensors and actuators. In order to comply with real-time and power-consumption constraints, these systems need to process a large amount of heterogeneous data from multiple sensors and take action (via actuators), which represents a problem as the resources of these systems have limitations in memory storage, bandwidth, and computational power. Field Programmable Gate Arrays (FPGAs) are programmable logic devices that offer high-speed parallel processing. FPGAs are particularly well-suited for applications that require real-time processing, high bandwidth, and low latency. One of the fundamental advantages of FPGAs is their flexibility in designing hardware tailored to specific needs, making them adaptable to a wide range of applications. They can be programmed to pre-process data close to sensors, which reduces the amount of data that needs to be transferred to other computing resources, improving overall system efficiency. Additionally, the reprogrammability of FPGAs enables them to be repurposed for different applications, providing a cost-effective solution that needs to adapt quickly to changing demands. FPGAs' performance per watt is close to that of Application-Specific Integrated Circuits (ASICs), with the added advantage of being reprogrammable. Despite all the advantages of FPGAs (e.g., energy efficiency, computing capabilities), the robotics community has not fully included them so far as part of their systems for several reasons. First, designing FPGA-based solutions requires hardware knowledge and longer development times as their programmability is more challenging than Central Processing Units (CPUs) or Graphics Processing Units (GPUs). Second, porting a robotics application (or parts of it) from software to an accelerator requires adequate interfaces between software and FPGAs. Third, the robotics workflow is already complex on its own, combining several fields such as mechanics, electronics, and software. There have been partial contributions in the state-of-the-art for FPGAs as part of robotics systems. However, a study of FPGAs as a whole for robotics systems is missing in the literature, which is the primary goal of this dissertation. Three main objectives have been established to accomplish this. (1) Define all components required for an FPGAs-based system for robotics applications as a whole. (2) Establish how all the defined components are related. (3) With the help of Model-Driven Engineering (MDE) techniques, generate these components, deploy them, and integrate them into existing solutions. The component-oriented approach proposed in this dissertation provides a proper solution for designing and implementing FPGA-based designs for robotics applications. The modular architecture, the tool 'FPGA Interfaces for Robotics Middlewares' (FIRM), and the toolchain 'FPGA Architectures for Robotics' (FAR) provide a set of tools and a comprehensive design process that enables the development of complex FPGA-based designs more straightforwardly and efficiently. The component-oriented approach contributed to the state-of-the-art in FPGA-based designs significantly for robotics applications and helps to promote their wider adoption and use by specialists with little FPGA knowledge