HERO: Heterogeneous Embedded Research Platform for Exploring RISC-V Manycore Accelerators on FPGA

Heterogeneous embedded systems on chip (HESoCs) co-integrate a standard host processor with programmable manycore accelerators (PMCAs) to combine general-purpose computing with domain-specific, efficient processing capabilities. While leading companies successfully advance their HESoC products, research lags behind due to the challenges of building a prototyping platform that unites an industry-standard host processor with an open research PMCA architecture. In this work we introduce HERO, an FPGA-based research platform that combines a PMCA composed of clusters of RISC-V cores, implemented as soft cores on an FPGA fabric, with a hard ARM Cortex-A multicore host processor. The PMCA architecture mapped on the FPGA is silicon-proven, scalable, configurable, and fully modifiable. HERO includes a complete software stack that consists of a heterogeneous cross-compilation toolchain with support for OpenMP accelerator programming, a Linux driver, and runtime libraries for both host and PMCA. HERO is designed to facilitate rapid exploration on all software and hardware layers: run-time behavior can be accurately analyzed by tracing events, and modifications can be validated through fully automated hard ware and software builds and executed tests. We demonstrate the usefulness of HERO by means of case studies from our research

Trusted Computing using Enhanced Manycore Architectures with Cryptoprocessors

International audienceManycore architectures correspond to a main evolution of computing systems due to their high processing power. Many applications can be executed in parallel which provides users with a very efficient technology. Cloud computing is one of the many domains where manycore architectures will play a major role. Thus, building secure manycore architectures is a critical issue. However a trusted platform based on manycore architectures is not available yet. In this paper we discuss the main challenges and some possible solutions to enhance manycore architectures with cryptoprocessor

Core Count vs Cache Size for Manycore Architectures in the Cloud

The number of cores which fit on a single chip is growing at an exponential rate while off-chip main memory bandwidth is growing at a linear rate at best. This core count to off-chip bandwidth disparity causes per-core memory bandwidth to decrease as process technology advances. Continuing per-core off-chip bandwidth reduction will cause multicore and manycore chip architects to rethink the optimal grain size of a core and the on-chip cache configuration in order to save main memory bandwidth. This work introduces an analytic model to study the tradeoffs of utilizing increased chip area for larger caches versus more cores. We focus this study on constructing manycore architectures well suited for the emerging application space of cloud computing where many independent applications are consolidated onto a single chip. This cloud computing application mix favors small, power-efficient cores. The model is exhaustively evaluated across a large range of cache and core-count configurations utilizing SPEC Int 2000 miss rates and CACTI timing and area models to determine the optimal cache configurations and the number of cores across four process nodes. The model maximizes aggregate computational throughput and is applied to SRAM and logic process DRAM caches. As an example, our study demonstrates that the optimal manycore configuration in the 32nm node for a 200 mm^2 die uses on the order of 158 cores, with each core containing a 64KB L1I cache, a 16KB L1D cache, and a 1MB L2 embedded-DRAM cache. This study finds that the optimal cache size will continue to grow as process technology advances, but the tradeoff between more cores and larger caches is a complex tradeoff in the face of limited off-chip bandwidth and the non-linearities of cache miss rates and memory controller queuing delay

Exploiting memory allocations in clusterized many-core architectures

Power-efficient architectures have become the most important feature required for future embedded systems. Modern designs, like those released on mobile devices, reveal that clusterization is the way to improve energy efficiency. However, such architectures are still limited by the memory subsystem (i.e., memory latency problems). This work investigates an alternative approach that exploits on-chip data locality to a large extent, through distributed shared memory systems that permit efficient reuse of on-chip mapped data in clusterized many-core architectures. First, this work reviews the current literature on memory allocations and explore the limitations of cluster-based many-core architectures. Then, several memory allocations are introduced and benchmarked scalability, performance and energy-wise, compared to the conventional centralized shared memory solution to reveal which memory allocation is the most appropriate for future mobile architectures. Our results show that distributed shared memory allocations bring performance gains and opportunities to reduce energy consumption

Conflict-Free Networks on Chip for Real Time Systems

[ES] La constante necesidad de un mayor rendimiento para cumplir con la gran demanda de potencia de cómputo de las nuevas aplicaciones, (ej. sistemas de conducción autónoma), obliga a la industria a apostar por la tecnología basada en Sistemas en Chip con Procesadores Multinúcleo (MPSoCs) en sus sistemas embebidos de seguridad-crítica. Los sistemas MPSoCs generalmente incluyen una red en el chip (NoC) para interconectar los núcleos de procesamiento entre ellos, con la memoria y con el resto de recursos compartidos. Desafortunadamente, el uso de las NoCs dificulta alcanzar la predecibilidad en el tiempo, ya que pueden aparecer conflictos en muchos puntos y de forma distribuida a nivel de red. Para afrontar este problema, en esta tesis se propone un nuevo paradigma de diseño para NoCs de tiempo real donde los conflictos en la red son eliminados por diseño. Este nuevo paradigma parte del Grafo de Dependencia de Canales (CDG) para evitar los conflictos de red de forma determinista. Nuestra solución es capaz de inyectar mensajes de forma natural usando un periodo TDM igual al límite teórico óptimo sin la necesidad de usar un proceso offline exigente computacionalmente. La red se ha integrado en un sistema multinúcleo basado en tiles y adaptado a su jerarquía de memoria. Como segunda contribución principal, proponemos un nuevo planificador dinámico y distribuido capaz de alcanzar un rendimiento pico muy cercanos a las NoC basadas en un diseño wormhole sin comprometer sus garantías de tiempo real. El planificador se basa en nuestro diseño de red para explotar sus propiedades clave. Los resultados de nuestra NoC muestran que nuestro diseño garantiza la predecibilidad en el tiempo evitando interferencias en la red entre múltiples aplicaciones ejecutándose concurrentemente. La red siempre garantiza el rendimiento y también mejora el rendimiento respecto al de las redes wormhole en una red 4 x 4 en un factor de 3,7x cuando se inyecta trafico para generar interferencias. En una red 8 x 8 las diferencias son incluso mayores. Además, la red obtiene un ahorro de área total del 10,79% frente a una implementación básica de una red wormhole. El planificador propuesto alcanza una mejora de rendimiento de 6,9x y 14,4x frente la versión básica de la red DCFNoC para redes en forma de malla de 16 y 64 nodos, respectivamente. Cuando lo comparamos frente a un conmutador estándar wormhole se preserva un rendimiento de red del 95% al mismo tiempo que preserva la estricta predecibilidad en el tiempo. Este logro abre la puerta a nuevos diseños de NoCs de alto rendimiento con predecibilidad en el tiempo. Como contribución final, construimos una taxonomía de NoCs basadas en TDM con propiedades de tiempo real. Con esta taxonomía realizamos un análisis exhaustivo para estudiar y comparar desde tiempos de respuesta, a implementaciones con bajo coste, pasando por soluciones de compromiso para diseños de NoCs de tiempo real. Como resultado, obtenemos nuevos diseños de NoCs basadas en TDM.[CA] La constant necessitat d'un major rendiment per a complir amb la gran demanda de potència de còmput de les noves aplicacions, (ex. sistemes de conducció autònoma), obliga la indústria a apostar per la tecnologia basada en Sistemes en Xip amb Processadors Multinucli (MPSoCs) en els seus sistemes embeguts de seguretat-crítica. Els sistemes MPSoCs generalment inclouen una xarxa en el xip (NoC) per a interconnectar els nuclis de processament entre ells, amb la memòria i amb la resta de recursos compartits. Desafortunadament, l'ús de les NoCs dificulta aconseguir la predictibilitat en el temps, ja que poden aparéixer conflictes en molts punts i de forma distribuïda a nivell de xarxa. Per a afrontar aquest problema, en aquesta tesi es proposa un nou paradigma de disseny per a NoCs de temps real on els conflictes en la xarxa són eliminats per disseny. Aquest nou paradigma parteix del Graf de Dependència de Canals (CDG) per a evitar els conflictes de xarxa de manera determinista. La nostra solució és capaç d'injectar missatges de mra natural fent ús d'un període TDM igual al límit teòric òptim sense la necessitat de fer ús d'un procés offline exigent computacionalment. La xarxa s'ha integrat en un sistema multinucli basat en tiles i adaptat a la seua jerarquia de memòria. Com a segona contribució principal, proposem un nou planificador dinàmic i distribuït capaç d'aconseguir un rendiment pic molt pròxims a les NoC basades en un disseny wormhole sense comprometre les seues garanties de temps real. El planificador es basa en el nostre disseny de xarxa per a explotar les seues propietats clau. Els resultats de la nostra NoC mostren que el nostre disseny garanteix la predictibilitat en el temps evitant interferències en la xarxa entre múltiples aplicacions executant-se concurrentment. La xarxa sempre garanteix el rendiment i també millora el rendiment respecte al de les xarxes wormhole en una xarxa 4 x 4 en un factor de 3,7x quan s'injecta trafic per a generar interferències. En una xarxa 8 x 8 les diferències són fins i tot majors. A més, la xarxa obté un estalvi d'àrea total del 10,79% front una implementació bàsica d'una xarxa wormhole. El planificador proposat aconsegueix una millora de rendiment de 6,9x i 14,4x front la versió bàsica de la xarxa DCFNoC per a xarxes en forma de malla de 16 i 64 nodes, respectivament. Quan ho comparem amb un commutador estàndard wormhole es preserva un rendiment de xarxa del 95% al mateix temps que preserva la estricta predictibilitat en el temps. Aquest assoliment obri la porta a nous dissenys de NoCs d'alt rendiment amb predictibilitat en el temps. Com a contribució final, construïm una taxonomia de NoCs basades en TDM amb propietats de temps real. Amb aquesta taxonomia realitzem una anàlisi exhaustiu per a estudiar i comparar des de temps de resposta, a implementacions amb baix cost, passant per solucions de compromís per a dissenys de NoCs de temps real. Com a resultat, obtenim nous dissenys de NoCs basades en TDM.[EN] The ever need for higher performance to cope with the high computational power demands of new applications (e.g autonomous driving systems), forces industry to support technology based on multi-processors system on chip (MPSoCs) in their safety-critical embedded systems. MPSoCs usually include a network-on-chip (NoC) to interconnect the cores between them and, with memory and the rest of shared resources. Unfortunately, the inclusion of NoCs difficults achieving time predictability as network-level conflicts may occur in many points in a distributed manner. To overcome this problem, this thesis proposes a new time-predictable NoC design paradigm where conflicts within the network are eliminated by design. This new paradigm builds on top of the Channel Dependency Graph (CDG) in order to deterministically avoid network conflicts. Our solution is able to naturally inject messages using a TDM period equal to the optimal theoretical bound without the need of using a computationally demanding offline process. The network is integrated in a tile-based manycore system and adapted to its memory hierarchy. As a second main contribution, we propose a novel distributed dynamic scheduler that is able to achieve peak performance close to a wormhole-based NoC design without compromising its real-time guarantees. The scheduler builds on top of our NoC design to exploit its key properties. The results of our NoC show that our design guarantees time predictability avoiding network interference among multiple running applications. The network always guarantees performance and also improves wormhole performance in a 4 x 4 setting by a factor of 3.7x when interference traffic is injected. For a 8 x 8 network differences are even larger. In addition, the network obtains a total area saving of 10.79% over a standard wormhole implementation. The proposed scheduler achieves an overall throughput improvement of 6.9x and 14.4x over a baseline conflict-free NoC for 16 and 64-node meshes, respectively. When compared against a standard wormhole router 95% of its network throughput is preserved while strict timing predictability is kept. This achievement opens the door to new high performance time predictable NoC designs. As a final contribution, we build a taxonomy of TDM-based NoCs with real-time properties. With this taxonomy we perform a comprehensive analysis to study and compare from response time specific, to low resource implementation cost, through trade-off solutions for real-time NoCs designs. As a result, we derive new TDM-based NoC designs.Picornell Sanjuan, T. (2021). Conflict-Free Networks on Chip for Real Time Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/177347TESI

Many-core and heterogeneous architectures: programming models and compilation toolchains

1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen677. INGEGNERIA INFORMATInopartially_openembargoed_20211002Barchi, Francesc

WiSync: an architecture for fast synchronization through on-chip wireless communication

In shared-memory multiprocessing, fine-grain synchronization is challenging because it requires frequent communication. As technology scaling delivers larger manycore chips, such pattern is expected to remain costly to support.; In this paper, we propose to address this challenge by using on-chip wireless communication. Each core has a transceiver and an antenna to communicate with all the other cores. This environment supports very low latency global communication. Our architecture, called WiSync, uses a per-core Broadcast Memory (BM). When a core writes to its BM, all the other 100+ BMs get updated in less than 10 processor cycles. We also use a second wireless channel with cheaper transfers to execute barriers efficiently. WiSync supports multiprogramming, virtual memory, and context switching. Our evaluation with simulations of 128-threaded kernels and 64-threaded applications shows that WiSync speeds-up synchronization substantially. Compared to using advanced conventional synchronization, WiSync attains an average speedup of nearly one order of magnitude for the kernels, and 1.12 for PARSEC and SPLASH-2.Peer ReviewedPostprint (author's final draft

Energy-efficient electrical and silicon-photonic networks in many core systems

Thesis (Ph.D.)--Boston UniversityDuring the past decade, the very large scale integration (VLSI) community has migrated towards incorporating multiple cores on a single chip to sustain the historic performance improvement in computing systems. As the core count continuously increases, the performance of network-on-chip (NoC), which is responsible for the communication between cores, caches and memory controllers, is increasingly becoming critical for sustaining the performance improvement. In this dissertation, we propose several methods to improve the energy efficiency of both electrical and silicon-photonic NoCs. Firstly, for electrical NoC, we propose a flow control technique, Express Virtual Channel with Taps (EVC-T), to transmit both broadcast and data packets efficiently in a mesh network. A low-latency notification tree network is included to maintain t he order of broadcast packets. The EVC-T technique improves the NoC latency by 24% and the system energy efficiency in terms of energy-delay product (EDP) by 13%. In the near future, the silicon-photonic links are projected to replace the electrical links for global on-chip communication due to their lower data-dependent power and higher bandwidth density, but the high laser power can more than offset these advantages. Therefore, we propose a silicon-photonic multi-bus NoC architecture and a methodology that can reduce the laser power by 49% on average through bandwidth reconfiguration at runtime based on the variations in bandwidth requirements of applications. We also propose a technique to reduce the laser power by dynamically activating/deactivating the 12 cache banks and switching ON/ OFF the corresponding silicon-photonic links in a crossbar NoC. This cache-reconfiguration based technique can save laser power by 23.8% and improves system EDP by 5.52% on average. In addition, we propose a methodology for placing and sharing on-chip laser sources by jointly considering the bandwidth requirements, thermal constraints and physical layout constraints. Our proposed methodology for placing and sharing of on-chip laser sources reduces laser power. In addition to reducing the laser power to improve the energy efficiency of silicon-photonic NoCs, we propose to leverage the large bandwidth provided by silicon-photonic NoC to share computing resources. The global sharing of floating-point units can save system area by 13.75% and system power by 10%

CAP Bench: a benchmark suite for performance and energy evaluation of low-power many-core processors

International audienceSUMMARY The constant need for faster and more energy-efficient processors has been stimulating the development of new architectures, such as low-power many-core architectures. Researchers aiming to study these architectures are challenged by peculiar characteristics of some components such as Networks-on-Chip and lack of specific tools to evaluate their performance. In this context, the goal of this paper is to present a benchmark suite to evaluate state-of-the-art low-power many-core architectures such as the Kalray MPPA-256 low-power processor, which features 256 compute cores in a single chip. The benchmark was designed and used to highlight important aspects and details that need to be considered when developing parallel applications for emerging low-power many-core architectures. As a result, this paper demonstrates that the benchmark offers a diverse suite of programs with regard to parallel patterns, job types, communication intensity and task load strategies, suitable for a broad understanding of performance and energy consumption of MPPA-256 and upcoming many-core architectures

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