Performance Implications of NoCs on 3D-Stacked Memories: Insights from the Hybrid Memory Cube

Memories that exploit three-dimensional (3D)-stacking technology, which integrate memory and logic dies in a single stack, are becoming popular. These memories, such as Hybrid Memory Cube (HMC), utilize a network-on-chip (NoC) design for connecting their internal structural organizations. This novel usage of NoC, in addition to aiding processing-in-memory capabilities, enables numerous benefits such as high bandwidth and memory-level parallelism. However, the implications of NoCs on the characteristics of 3D-stacked memories in terms of memory access latency and bandwidth have not been fully explored. This paper addresses this knowledge gap by (i) characterizing an HMC prototype on the AC-510 accelerator board and revealing its access latency behaviors, and (ii) by investigating the implications of such behaviors on system and software designs

A Construction Kit for Efficient Low Power Neural Network Accelerator Designs

Implementing embedded neural network processing at the edge requires efficient hardware acceleration that couples high computational performance with low power consumption. Driven by the rapid evolution of network architectures and their algorithmic features, accelerator designs are constantly updated and improved. To evaluate and compare hardware design choices, designers can refer to a myriad of accelerator implementations in the literature. Surveys provide an overview of these works but are often limited to system-level and benchmark-specific performance metrics, making it difficult to quantitatively compare the individual effect of each utilized optimization technique. This complicates the evaluation of optimizations for new accelerator designs, slowing-down the research progress. This work provides a survey of neural network accelerator optimization approaches that have been used in recent works and reports their individual effects on edge processing performance. It presents the list of optimizations and their quantitative effects as a construction kit, allowing to assess the design choices for each building block separately. Reported optimizations range from up to 10'000x memory savings to 33x energy reductions, providing chip designers an overview of design choices for implementing efficient low power neural network accelerators

Experimental Evaluation and Comparison of Time-Multiplexed Multi-FPGA Routing Architectures

Emulating large complex designs require multi-FPGA systems (MFS). However, inter-FPGA communication is confronted by the challenge of lack of interconnect capacity due to limited number of FPGA input/output (I/O) pins. Serializing parallel signals onto a single trace effectively addresses the limited I/O pin obstacle. Besides the multiplexing scheme and multiplexing ratio (number of inter-FPGA signals per trace), the choice of the MFS routing architecture also affect the critical path latency. The routing architecture of an MFS is the interconnection pattern of FPGAs, fixed wires and/or programmable interconnect chips. Performance of existing MFS routing architectures is also limited by off-chip interface selection. In this dissertation we proposed novel 2D and 3D latency-optimized time-multiplexed MFS routing architectures. We used rigorous experimental approach and real sequential benchmark circuits to evaluate and compare the proposed and existing MFS routing architectures. This research provides a new insight into the encouraging effects of using off-chip optical interface and three dimensional MFS routing architectures. The vertical stacking results in shorter off-chip links improving the overall system frequency with the additional advantage of smaller footprint area. The proposed 3D architectures employed serialized interconnect between intra-plane and inter-plane FPGAs to address the pin limitation problem. Additionally, all off-chip links are replaced by optical fibers that exhibited latency improvement and resulted in faster MFS. Results indicated that exploiting third dimension provided latency and area improvements as compared to 2D MFS. We also proposed latency-optimized planar 2D MFS architectures in which electrical interconnections are replaced by optical interface in same spatial distribution. Performance evaluation and comparison showed that the proposed architectures have reduced critical path delay and system frequency improvement as compared to conventional MFS. We also experimentally evaluated and compared the system performance of three inter-FPGA communication schemes i.e. Logic Multiplexing, SERDES and MGT in conjunction with two routing architectures i.e. Completely Connected Graph (CCG) and TORUS. Experimental results showed that SERDES attained maximum frequency than the other two schemes. However, for very high multiplexing ratios, the performance of SERDES & MGT became comparable

Improving the Scalability of High Performance Computer Systems

Improving the performance of future computing systems will be based upon the ability of increasing the scalability of current technology. New paths need to be explored, as operating principles that were applied up to now are becoming irrelevant for upcoming computer architectures. It appears that scaling the number of cores, processors and nodes within an system represents the only feasible alternative to achieve Exascale performance. To accomplish this goal, we propose three novel techniques addressing different layers of computer systems. The Tightly Coupled Cluster technique significantly improves the communication for inter node communication within compute clusters. By improving the latency by an order of magnitude over existing solutions the cost of communication is considerably reduced. This enables to exploit fine grain parallelism within applications, thereby, extending the scalability considerably. The mechanism virtually moves the network interconnect into the processor, bypassing the latency of the I/O interface and rendering protocol conversions unnecessary. The technique is implemented entirely through firmware and kernel layer software utilizing off-the-shelf AMD processors. We present a proof-of-concept implementation and real world benchmarks to demonstrate the superior performance of our technique. In particular, our approach achieves a software-to-software communication latency of 240 ns between two remote compute nodes. The second part of the dissertation introduces a new framework for scalable Networks-on-Chip. A novel rapid prototyping methodology is proposed, that accelerates the design and implementation substantially. Due to its flexibility and modularity a large application space is covered ranging from Systems-on-chip, to high performance many-core processors. The Network-on-Chip compiler enables to generate complex networks in the form of synthesizable register transfer level code from an abstract design description. Our engine supports different target technologies including Field Programmable Gate Arrays and Application Specific Integrated Circuits. The framework enables to build large designs while minimizing development and verification efforts. Many topologies and routing algorithms are supported by partitioning the tasks into several layers and by the introduction of a protocol agnostic architecture. We provide a thorough evaluation of the design that shows excellent results regarding performance and scalability. The third part of the dissertation addresses the Processor-Memory Interface within computer architectures. The increasing compute power of many-core processors, leads to an equally growing demand for more memory bandwidth and capacity. Current processor designs exhibit physical limitations that restrict the scalability of main memory. To address this issue we propose a memory extension technique that attaches large amounts of DRAM memory to the processor via a low pin count interface using high speed serial transceivers. Our technique transparently integrates the extension memory into the system architecture by providing full cache coherency. Therefore, applications can utilize the memory extension by applying regular shared memory programming techniques. By supporting daisy chained memory extension devices and by introducing the asymmetric probing approach, the proposed mechanism ensures high scalability. We furthermore propose a DMA offloading technique to improve the performance of the processor memory interface. The design has been implemented in a Field Programmable Gate Array based prototype. Driver software and firmware modifications have been developed to bring up the prototype in a Linux based system. We show microbenchmarks that prove the feasibility of our design

Méthodologies de conception ASIC pour des systèmes sur puce 3D hétérogènes à base de réseaux sur puce 3D

Dans cette thèse, nous étudions les architectures 3D NoC grâce à des implémentations de conception physiques en utilisant la technologie 3D réel mis en oeuvre dans l'industrie. Sur la base des listes d'interconnexions en déroute, nous procédons à l'analyse des performances d'évaluer le bénéfice de l'architecture 3D par rapport à sa mise en oeuvre 2D. Sur la base du flot de conception 3D proposé en se concentrant sur la vérification temporelle tirant parti de l'avantage du retard négligeable de la structure de microbilles pour les connexions verticales, nous avons mené techniques de partitionnement de NoC 3D basé sur l'architecture MPSoC y compris empilement homogène et hétérogène en utilisant Tezzaron 3D IC technlogy. Conception et mise en oeuvre de compromis dans les deux méthodes de partitionnement est étudiée pour avoir un meilleur aperçu sur l'architecture 3D de sorte qu'il peut être exploitée pour des performances optimales. En utilisant l'approche 3D homogène empilage, NoC topologies est explorée afin d'identifier la meilleure topologie entre la topologie 2D et 3D pour la mise en œuvre MPSoC 3D sous l'hypothèse que les chemins critiques est fondée sur les liens inter-routeur. Les explorations architecturales ont également examiné les différentes technologies de traitement. mettant en évidence l'effet de la technologie des procédés à la performance d'architecture 3D en particulier pour l'interconnexion dominant du design. En outre, nous avons effectué hétérogène 3D d'empilage pour la mise en oeuvre MPSoC avec l'approche GALS de style et présenté plusieurs analyses de conception physiques connexes concernant la conception 3D et la mise en œuvre MPSoC utilisant des outils de CAO 2D. Une analyse plus approfondie de l'effet microbilles pas à la performance de l'architecture 3D à l'aide face-à-face d'empilement est également signalé l'identification des problèmes et des limitations à prendre en considération pendant le processus de conception.In this thesis, we study the exploration 3D NoC architectures through physical design implementations using real 3D technology used in the industry. Based on the proposed 3D design flow focusing on timing verification by leveraging the benefit of negligible delay of microbumps structure for vertical connections, we have conducted partitioning techniques for 3D NoC-based MPSoC architecture including homogeneous and heterogeneous stacking using Tezzaron 3D IC technlogy. Design and implementation trade-off in both partitioning methods is investigated to have better insight about 3D architecture so that it can be exploited for optimal performance. Using homogeneous 3D stacking approach, NoC architectures are explored to identify the best topology between 2D and 3D topology for 3D MPSoC implementation. The architectural explorations have also considered different process technologies highlighting the wire delay effect to the 3D architecture performance especially for interconnect-dominated design. Additionally, we performed heterogeneous 3D stacking of NoC-based MPSoC implementation with GALS style approach and presented several physical designs related analyses regarding 3D MPSoC design and implementation using 2D EDA tools. Finally we conducted an exploration of 2D EDA tool on different 3D architecture to evaluate the impact of 2D EDA tools on the 3D architecture performance. Since there is no commercialize 3D design tool until now, the experiment is important on the basis that designing 3D architecture using 2D EDA tools does not have a strong and direct impact to the 3D architecture performance mainly because the tools is dedicated for 2D architecture design.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

On Energy Efficient Computing Platforms

In accordance with the Moore's law, the increasing number of on-chip integrated transistors has enabled modern computing platforms with not only higher processing power but also more affordable prices. As a result, these platforms, including portable devices, work stations and data centres, are becoming an inevitable part of the human society. However, with the demand for portability and raising cost of power, energy efficiency has emerged to be a major concern for modern computing platforms. As the complexity of on-chip systems increases, Network-on-Chip (NoC) has been proved as an efficient communication architecture which can further improve system performances and scalability while reducing the design cost. Therefore, in this thesis, we study and propose energy optimization approaches based on NoC architecture, with special focuses on the following aspects. As the architectural trend of future computing platforms, 3D systems have many bene ts including higher integration density, smaller footprint, heterogeneous integration, etc. Moreover, 3D technology can signi cantly improve the network communication and effectively avoid long wirings, and therefore, provide higher system performance and energy efficiency. With the dynamic nature of on-chip communication in large scale NoC based systems, run-time system optimization is of crucial importance in order to achieve higher system reliability and essentially energy efficiency. In this thesis, we propose an agent based system design approach where agents are on-chip components which monitor and control system parameters such as supply voltage, operating frequency, etc. With this approach, we have analysed the implementation alternatives for dynamic voltage and frequency scaling and power gating techniques at different granularity, which reduce both dynamic and leakage energy consumption. Topologies, being one of the key factors for NoCs, are also explored for energy saving purpose. A Honeycomb NoC architecture is proposed in this thesis with turn-model based deadlock-free routing algorithms. Our analysis and simulation based evaluation show that Honeycomb NoCs outperform their Mesh based counterparts in terms of network cost, system performance as well as energy efficiency.Siirretty Doriast

Design and Code Optimization for Systems with Next-generation Racetrack Memories

With the rise of computationally expensive application domains such as machine learning, genomics, and fluids simulation, the quest for performance and energy-efficient computing has gained unprecedented momentum. The significant increase in computing and memory devices in modern systems has resulted in an unsustainable surge in energy consumption, a substantial portion of which is attributed to the memory system. The scaling of conventional memory technologies and their suitability for the next-generation system is also questionable. This has led to the emergence and rise of nonvolatile memory ( NVM ) technologies. Today, in different development stages, several NVM technologies are competing for their rapid access to the market. Racetrack memory ( RTM ) is one such nonvolatile memory technology that promises SRAM -comparable latency, reduced energy consumption, and unprecedented density compared to other technologies. However, racetrack memory ( RTM ) is sequential in nature, i.e., data in an RTM cell needs to be shifted to an access port before it can be accessed. These shift operations incur performance and energy penalties. An ideal RTM , requiring at most one shift per access, can easily outperform SRAM . However, in the worst-cast shifting scenario, RTM can be an order of magnitude slower than SRAM . This thesis presents an overview of the RTM device physics, its evolution, strengths and challenges, and its application in the memory subsystem. We develop tools that allow the programmability and modeling of RTM -based systems. For shifts minimization, we propose a set of techniques including optimal, near-optimal, and evolutionary algorithms for efficient scalar and instruction placement in RTMs . For array accesses, we explore schedule and layout transformations that eliminate the longer overhead shifts in RTMs . We present an automatic compilation framework that analyzes static control flow programs and transforms the loop traversal order and memory layout to maximize accesses to consecutive RTM locations and minimize shifts. We develop a simulation framework called RTSim that models various RTM parameters and enables accurate architectural level simulation. Finally, to demonstrate the RTM potential in non-Von-Neumann in-memory computing paradigms, we exploit its device attributes to implement logic and arithmetic operations. As a concrete use-case, we implement an entire hyperdimensional computing framework in RTM to accelerate the language recognition problem. Our evaluation shows considerable performance and energy improvements compared to conventional Von-Neumann models and state-of-the-art accelerators

Cross-Layer Pathfinding for Off-Chip Interconnects

Off-chip interconnects for integrated circuits (ICs) today induce a diverse design space, spanning many different applications that require transmission of data at various bandwidths, latencies and link lengths. Off-chip interconnect design solutions are also variously sensitive to system performance, power and cost metrics, while also having a strong impact on these metrics. The costs associated with off-chip interconnects include die area, package (PKG) and printed circuit board (PCB) area, technology and bill of materials (BOM). Choices made regarding off-chip interconnects are fundamental to product definition, architecture, design implementation and technology enablement. Given their cross-layer impact, it is imperative that a cross-layer approach be employed to architect and analyze off-chip interconnects up front, so that a top-down design flow can comprehend the cross-layer impacts and correctly assess the system performance, power and cost tradeoffs for off-chip interconnects. Chip architects are not exposed to all the tradeoffs at the physical and circuit implementation or technology layers, and often lack the tools to accurately assess off-chip interconnects. Furthermore, the collaterals needed for a detailed analysis are often lacking when the chip is architected; these include circuit design and layout, PKG and PCB layout, and physical floorplan and implementation. To address the need for a framework that enables architects to assess the system-level impact of off-chip interconnects, this thesis presents power-area-timing (PAT) models for off-chip interconnects, optimization and planning tools with the appropriate abstraction using these PAT models, and die/PKG/PCB co-design methods that help expose the off-chip interconnect cross-layer metrics to the die/PKG/PCB design flows. Together, these models, tools and methods enable cross-layer optimization that allows for a top-down definition and exploration of the design space and helps converge on the correct off-chip interconnect implementation and technology choice. The tools presented cover off-chip memory interfaces for mobile and server products, silicon photonic interfaces, 2.5D silicon interposers and 3D through-silicon vias (TSVs). The goal of the cross-layer framework is to assess the key metrics of the interconnect (such as timing, latency, active/idle/sleep power, and area/cost) at an appropriate level of abstraction by being able to do this across layers of the design flow. In additional to signal interconnect, this thesis also explores the need for such cross-layer pathfinding for power distribution networks (PDN), where the system-on-chip (SoC) floorplan and pinmap must be optimized before the collateral layouts for PDN analysis are ready. Altogether, the developed cross-layer pathfinding methodology for off-chip interconnects enables more rapid and thorough exploration of a vast design space of off-chip parallel and serial links, inter-die and inter-chiplet links and silicon photonics. Such exploration will pave the way for off-chip interconnect technology enablement that is optimized for system needs. The basis of the framework can be extended to cover other interconnect technology as well, since it fundamentally relates to system-level metrics that are common to all off-chip interconnects