A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multi-core neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.Comment: 17 pages, 14 figure

Extending the performance of hybrid NoCs beyond the limitations of network heterogeneity

To meet the performance and scalability demands of the fast-paced technological growth towards exascale and Big-Data processing with the performance bottleneck of conventional metal based interconnects (wireline), alternative interconnect fabrics such as inhomogeneous three-dimensional integrated Network-on-Chip (3D NoC) and hybrid wired-wireless Network-on-Chip (WiNoC) have emanated as a cost-effective solution for emerging System-on-Chip (SoC) design. However, these interconnects trade-off optimized performance for cost by restricting the number of area and power hungry 3D routers and wireless nodes. Moreover, the non-uniform distributed traffic in chip multiprocessor (CMP) demands an on-chip communication infrastructure which can avoid congestion under high traffic conditions while possessing minimal pipeline delay at low-load conditions. To this end, in this paper, we propose a low-latency adaptive router with a low-complexity single-cycle bypassing mechanism to alleviate the performance degradation due to the slow 2D routers in such emerging hybrid NoCs. The proposed router transmits a flit using dimension-ordered routing (DoR) in the bypass datapath at low-loads. When the output port required for intra-dimension bypassing is not available, the packet is routed adaptively to avoid congestion. The router also has a simplified virtual channel allocation (VA) scheme that yields a non-speculative low-latency pipeline. By combining the low-complexity bypassing technique with adaptive routing, the proposed router is able balance the traffic in hybrid NoCs to achieve low-latency communication under various traffic loads. Simulation shows that, the proposed router can reduce applications’ execution time by an average of 16.9% compared to low-latency routers such as SWIFT. By reducing the latency between 2D routers (or wired nodes) and 3D routers (or wireless nodes) the proposed router can improve performance efficiency in terms of average packet delay by an average of 45% (or 50%) in 3D NoCs (or WiNoCs)

Studies on Core-Based Testing of System-on-Chips Using Functional Bus and Network-on-Chip Interconnects

The tests of a complex system such as a microprocessor-based system-onchip (SoC) or a network-on-chip (NoC) are difficult and expensive. In this thesis, we propose three core-based test methods that reuse the existing functional interconnects-a flat bus, hierarchical buses of multiprocessor SoC's (MPSoC), and a N oC-in order to avoid the silicon area cost of a dedicated test access mechanism (TAM). However, the use of functional interconnects as functional TAM's introduces several new problems. During tests, the interconnects-including the bus arbitrator, the bus bridges, and the NoC routers-operate in the functional mode to transport the test stimuli and responses, while the core under tests (CUT) operate in the test mode. Second, the test data is transported to the CUT through the functional bus, and not directly to the test port. Therefore, special core test wrappers that can provide the necessary control signals required by the different functional interconnect are proposed. We developed two types of wrappers, one buffer-based wrapper for the bus-based systems and another pair of complementary wrappers for the NoCbased systems. Using the core test wrappers, we propose test scheduling schemes for the three functionally different types of interconnects. The test scheduling scheme for a flat bus is developed based on an efficient packet scheduling scheme that minimizes both the buffer sizes and the test time under a power constraint. The schedulingscheme is then extended to take advantage of the hierarchical bus architecture of the MPSoC systems. The third test scheduling scheme based on the bandwidth sharing is developed specifically for the NoC-based systems. The test scheduling is performed under the objective of co-optimizing the wrapper area cost and the resulting test application time using the two complementary NoC wrappers. For each of the proposed methodology for the three types of SoC architec .. ture, we conducted a thorough experimental evaluation in order to verify their effectiveness compared to other methods

Floorplan-Aware High Performance NoC Design

Las actuales arquitecturas de m�ltiples n�cleos como los chip multiprocesadores (CMP) y soluciones multiprocesador para sistemas dentro del chip (MPSoCs) han adoptado a las redes dentro del chip (NoC) como elemento -ptimo para la inter-conexi-n de los diversos elementos de dichos sistemas. En este sentido, fabricantes de CMPs y MPSoCs han adoptado NoCs sencillas, generalmente con una topolog'a en malla o anillo, ya que son suficientes para satisfacer las necesidades de los sistemas actuales. Sin embargo a medida que los requerimientos del sistema -- baja latencia y alto rendimiento -- se hacen m�s exigentes, estas redes tan simples dejan de ser una soluci-n real. As', la comunidad investigadora ha propuesto y analizado NoCs m�s complejas. No obstante, estas soluciones son m�s dif'ciles de implementar -- especialmente los enlaces largos -- haciendo que este tipo de topolog'as complejas sean demasiado costosas o incluso inviables. En esta tesis, presentamos una metodolog'a de dise-o que minimiza la p�rdida de prestaciones de la red debido a su implementaci-n real. Los principales problemas que se encuentran al implementar una NoC son los conmutadores y los enlaces largos. En esta tesis, el conmutador se ha hecho modular, es decir, formado como uni-n de m-dulos m�s peque-os. En nuestro caso, los m-dulos son id�nticos, donde cada m-dulo es capaz de arbitrar, conmutar, y almacenar los mensajes que le llegan. Posteriormente, flexibilizamos la colocaci-n de estos m-dulos en el chip, permitiendo que m-dulos de un mismo conmutador est�n distribuidos por el chip. Esta metodolog'a de dise-o la hemos aplicado a diferentes escenarios. Primeramente, hemos introducido nuestro conmutador modular en NoCs con topolog'as conocidas como la malla 2D. Los resultados muestran como la modularidad y la distribuci-n del conmutador reducen la latencia y el consumo de potencia de la red. En segundo lugar, hemos utilizado nuestra metodolog'a de dise-o para implementar un crossbar distribuidRoca Pérez, A. (2012). Floorplan-Aware High Performance NoC Design [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17844Palanci

Adaptive memory-side last-level GPU caching

Emerging GPU applications exhibit increasingly high computation demands which has led GPU manufacturers to build GPUs with an increasingly large number of streaming multiprocessors (SMs). Providing data to the SMs at high bandwidth puts significant pressure on the memory hierarchy and the Network-on-Chip (NoC). Current GPUs typically partition the memory-side last-level cache (LLC) in equally-sized slices that are shared by all SMs. Although a shared LLC typically results in a lower miss rate, we find that for workloads with high degrees of data sharing across SMs, a private LLC leads to a significant performance advantage because of increased bandwidth to replicated cache lines across different LLC slices. In this paper, we propose adaptive memory-side last-level GPU caching to boost performance for sharing-intensive workloads that need high bandwidth to read-only shared data. Adaptive caching leverages a lightweight performance model that balances increased LLC bandwidth against increased miss rate under private caching. In addition to improving performance for sharing-intensive workloads, adaptive caching also saves energy in a (co-designed) hierarchical two-stage crossbar NoC by power-gating and bypassing the second stage if the LLC is configured as a private cache. Our experimental results using 17 GPU workloads show that adaptive caching improves performance by 28.1% on average (up to 38.1%) compared to a shared LLC for sharing-intensive workloads. In addition, adaptive caching reduces NoC energy by 26.6% on average (up to 29.7%) and total system energy by 6.1% on average (up to 27.2%) when configured as a private cache. Finally, we demonstrate through a GPU NoC design space exploration that a hierarchical two-stage crossbar is both more power- and area-efficient than full and concentrated crossbars with the same bisection bandwidth, thus providing a low-cost cooperative solution to exploit workload sharing behavior in memory-side last-level caches

Doctor of Philosophy

dissertationPortable electronic devices will be limited to available energy of existing battery chemistries for the foreseeable future. However, system-on-chips (SoCs) used in these devices are under a demand to offer more functionality and increased battery life. A difficult problem in SoC design is providing energy-efficient communication between its components while maintaining the required performance. This dissertation introduces a novel energy-efficient network-on-chip (NoC) communication architecture. A NoC is used within complex SoCs due it its superior performance, energy usage, modularity, and scalability over traditional bus and point-to-point methods of connecting SoC components. This is the first academic research that combines asynchronous NoC circuits, a focus on energy-efficient design, and a software framework to customize a NoC for a particular SoC. Its key contribution is demonstrating that a simple, asynchronous NoC concept is a good match for low-power devices, and is a fruitful area for additional investigation. The proposed NoC is energy-efficient in several ways: simple switch and arbitration logic, low port radix, latch-based router buffering, a topology with the minimum number of 3-port routers, and the asynchronous advantages of zero dynamic power consumption while idle and the lack of a clock tree. The tool framework developed for this work uses novel methods to optimize the topology and router oorplan based on simulated annealing and force-directed movement. It studies link pipelining techniques that yield improved throughput in an energy-efficient manner. A simulator is automatically generated for each customized NoC, and its traffic generators use a self-similar message distribution, as opposed to Poisson, to better match application behavior. Compared to a conventional synchronous NoC, this design is superior by achieving comparable message latency with half the energy

Hierarchical Agent-based Adaptation for Self-Aware Embedded Computing Systems

Siirretty Doriast