Efficient and predictable high-speed storage access for real-time embedded systems

As the speed, size, reliability and power efficiency of non-volatile storage media increases, and the data demands of many application domains grow, operating systems are being put under escalating pressure to provide high-speed access to storage. Traditional models of storage access assume devices to be slow, expecting plenty of slack time in which to process data between requests being serviced, and that all significant variations in timing will be down to the storage device itself. Modern high-speed storage devices break this assumption, causing storage applications to become processor-bound, rather than I/O-bound, in an increasing number of situations. This is especially an issue in real-time embedded systems, where limited processing resources and strict timing and predictability requirements amplify any issues caused by the complexity of the software storage stack. This thesis explores the issues related to accessing high-speed storage from real-time embedded systems, providing a thorough analysis of storage operations based on metrics relevant to the area. From this analysis, a number of alternative storage architectures are proposed and explored, showing that a simpler, more direct path from applications to storage can have a positive impact on efficiency and predictability in such systems

METICULOUS: An FPGA-based Main Memory Emulator for System Software Studies

Due to the scaling problem of the DRAM technology, non-volatile memory devices, which are based on different principle of operation than DRAM, are now being intensively developed to expand the main memory of computers. Disaggregated memory is also drawing attention as an emerging technology to scale up the main memory. Although system software studies need to discuss management mechanisms for the new main memory designs incorporating such emerging memory systems, there are no feasible memory emulation mechanisms that efficiently work for large-scale, privileged programs such as operating systems and hypervisors. In this paper, we propose an FPGA-based main memory emulator for system software studies on new main memory systems. It can emulate the main memory incorporating multiple memory regions with different performance characteristics. For the address region of each memory device, it emulates the latencies, bandwidths and bit-flip error rates of read/write operations, respectively. The emulator is implemented at the hardware module of an off-the-self FPGA System-on-Chip board. Any privileged/unprivileged software programs running on its powerful 64-bit CPU cores can access emulated main memory devices at a practical speed through the exactly same interface as normal DRAM main memory. We confirmed that the emulator transparently worked for CPU cores and successfully changed the performance of a memory region according to given emulation parameters; for example, the latencies measured by CPU cores were exactly proportional to the latencies inserted by the emulator, involving the minimum overhead of approximately 240 ns. As a preliminary use case, we confirmed that the emulator allows us to change the bandwidth limit and the inserted latency individually for unmodified software programs, making discussions on latency sensitivity much easier

Energy-Aware Data Movement In Non-Volatile Memory Hierarchies

While technology scaling enables increased density for memory cells, the intrinsic high leakage power of conventional CMOS technology and the demand for reduced energy consumption inspires the use of emerging technology alternatives such as eDRAM and Non-Volatile Memory (NVM) including STT-MRAM, PCM, and RRAM. The utilization of emerging technology in Last Level Cache (LLC) designs which occupies a signifcant fraction of total die area in Chip Multi Processors (CMPs) introduces new dimensions of vulnerability, energy consumption, and performance delivery. To be specific, a part of this research focuses on eDRAM Bit Upset Vulnerability Factor (BUVF) to assess vulnerable portion of the eDRAM refresh cycle where the critical charge varies depending on the write voltage, storage and bit-line capacitance. This dissertation broaden the study on vulnerability assessment of LLC through investigating the impact of Process Variations (PV) on narrow resistive sensing margins in high-density NVM arrays, including on-chip cache and primary memory. Large-latency and power-hungry Sense Amplifers (SAs) have been adapted to combat PV in the past. Herein, a novel approach is proposed to leverage the PV in NVM arrays using Self-Organized Sub-bank (SOS) design. SOS engages the preferred SA alternative based on the intrinsic as-built behavior of the resistive sensing timing margin to reduce the latency and power consumption while maintaining acceptable access time. On the other hand, this dissertation investigates a novel technique to prioritize the service to 1) Extensive Read Reused Accessed blocks of the LLC that are silently dropped from higher levels of cache, and 2) the portion of the working set that may exhibit distant re-reference interval in L2. In particular, we develop a lightweight Multi-level Access History Profiler to effciently identify ERRA blocks through aggregating the LLC block addresses tagged with identical Most Signifcant Bits into a single entry. Experimental results indicate that the proposed technique can reduce the L2 read miss ratio by 51.7% on average across PARSEC and SPEC2006 workloads. In addition, this dissertation will broaden and apply advancements in theories of subspace recovery to pioneer computationally-aware in-situ operand reconstruction via the novel Logic In Interconnect (LI2) scheme. LI2 will be developed, validated, and re?ned both theoretically and experimentally to realize a radically different approach to post-Moore\u27s Law computing by leveraging low-rank matrices features offering data reconstruction instead of fetching data from main memory to reduce energy/latency cost per data movement. We propose LI2 enhancement to attain high performance delivery in the post-Moore\u27s Law era through equipping the contemporary micro-architecture design with a customized memory controller which orchestrates the memory request for fetching low-rank matrices to customized Fine Grain Reconfigurable Accelerator (FGRA) for reconstruction while the other memory requests are serviced as before. The goal of LI2 is to conquer the high latency/energy required to traverse main memory arrays in the case of LLC miss, by using in-situ construction of the requested data dealing with low-rank matrices. Thus, LI2 exchanges a high volume of data transfers with a novel lightweight reconstruction method under specific conditions using a cross-layer hardware/algorithm approach

Um framework para a avaliação de segurança de hardware

Orientador: Ricardo DahabDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O hardware de sistemas computacionais possui uma função crítica na segurança de sistemas operacionais e aplicativos. Além de prover funcionalidades-padrão, tal como o nível de privilégio de execução, o hardware também pode oferecer suporte a criptografia, boot seguro, execução segura, e outros. Com o fim de garantir que essas funcionalidades de segurança irão operar corretamente quando juntas dentro de um sistema, e de que o sistema é seguro como um todo, é necessário avaliar a segurança da arquitetura de todo sistema, durante o ciclo de desenvolvimento do hardware. Neste trabalho, iniciamos pela pesquisa dos diferentes tipos existentes de vulnerabilidades de hardware, e propomos uma taxonomia para classificá-los. Nossa taxonomia é capaz de classificar as vulnerabilidades de acordo com o ponto no qual elas foram inseridas, dentro do ciclo de desenvolvimento. Ela também é capaz de separar as vulnerabilidades de hardware daquelas de software que apenas se aproveitam de funcionalidades-padrão do hardware. Focando em um tipo específico de vulnerabilidade - aquelas relacionadas à arquitetura - apresentamos um método para a avaliação de sistemas de hardware utilizando a metodologia de Assurance Cases. Essa metodologia tem sido usada com sucesso para a análise de segurança física e, tanto quanto saibamos, não há notícias de seu uso para a análise de segurança de hardware. Utilizando esse método, pudemos identificar corretamente as vulnerabilidades de sistemas reais. Por fim, apresentamos uma prova de conceito de uma ferramenta para guiar e automatizar parte do processo de análise que foi proposto. A partir de uma descrição padronizada de uma arquitetura de hardware, a ferramenta aplica uma série de regras de um sistema especialista e gera um relatório de Assurance Case com as possíveis vulnerabilidades do sistema-alvo. Aplicamos a ferramenta aos sistemas estudados e pudemos identificar com sucesso as vulnerabilidades conhecidas, assim como outras possíveis vulnerabilidadesAbstract: The hardware of computer systems plays a critical role in the security of operating systems and applications. Besides providing standard features such as execution privilege levels, it may also offer support for encryption, secure execution, secure boot, and others. In order to guarantee that these security features work correctly when inside a system, and that the system is secure as a whole, it is necessary to evaluate the security of the architecture during the hardware development life-cycle. In this work, we start by exploring the different types of existing hardware vulnerabilities and propose a taxonomy for classifying them. Our taxonomy is able to classify vulnerabilities according to when they were created during the development life-cycle, as well as separating real hardware vulnerabilities from software vulnerabilities that leverage standard hardware features. Focusing on a specific type of vulnerability - the architecture-related ones, we present a method for evaluating hardware systems using the Assurance Case methodology. This methodology has been used successfully for safety analysis, and to our best knowledge there are no reports of its use for hardware security analysis. Using this method, we were able to correctly identify the vulnerabilities of real-world systems. Lastly, we present the proof-of-concept of a tool for guiding and automating part of the proposed analysis methodology. Starting from a standardized hardware architecture description, the tool applies a set of expert system rules, and generates an Assurance Case report that contains the possible security vulnerabilities of a system. We were able to apply the tool to the studied systems, and correctly identify their known vulnerabilities, as well as other possible vulnerabilitiesMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

TSV placement optimization for liquid cooled 3D-ICs with emerging NVMs

Three dimensional integrated circuits (3D-ICs) are a promising solution to the performance bottleneck in planar integrated circuits. One of the salient features of 3D-ICs is their ability to integrate heterogeneous technologies such as emerging non-volatile memories (NVMs) in a single chip. However, thermal management in 3D-ICs is a significant challenge, owing to the high heat flux (~ 250 W/cm2). Several research groups have focused either on run-time or design-time mechanisms to reduce the heat flux and did not consider 3D-ICs with heterogeneous stacks. The goal of this work is to achieve a balanced thermal gradient in 3D-ICs, while reducing the peak temperatures. In this research, placement algorithms for design-time optimization and choice of appropriate cooling mechanisms for run-time modulation of temperature are proposed. Specifically, an architectural framework which introduce weight-based simulated annealing (WSA) algorithm for thermal-aware placement of through silicon vias (TSVs) with inter-tier liquid cooling is proposed for design-time. In addition, integrating a dedicated stack of emerging NVMs such as RRAM, PCRAM and STTRAM, a run-time simulation framework is developed to analyze the thermal and performance impact of these NVMs in 3D-MPSoCs with inter-tier liquid cooling. Experimental results of WSA algorithm implemented on MCNC91 and GSRC benchmarks demonstrate up to 11 K reduction in the average temperature across the 3D-IC chip. In addition, power density arrangement in WSA improved the uniformity by 5%. Furthermore, simulation results of PARSEC benchmarks with NVM L2 cache demonstrates a temperature reduction of 12.5 K (RRAM) compared to SRAM in 3D-ICs. Especially, RRAM has proved to be thermally efficient replacement for SRAM with 34% lower energy delay product (EDP) and 9.7 K average temperature reduction

Memory Subsystem Optimization Techniques for Modern High-Performance General-Purpose Processors

abstract: General-purpose processors propel the advances and innovations that are the subject of humanity’s many endeavors. Catering to this demand, chip-multiprocessors (CMPs) and general-purpose graphics processing units (GPGPUs) have seen many high-performance innovations in their architectures. With these advances, the memory subsystem has become the performance- and energy-limiting aspect of CMPs and GPGPUs alike. This dissertation identifies and mitigates the key performance and energy-efficiency bottlenecks in the memory subsystem of general-purpose processors via novel, practical, microarchitecture and system-architecture solutions. Addressing the important Last Level Cache (LLC) management problem in CMPs, I observe that LLC management decisions made in isolation, as in prior proposals, often lead to sub-optimal system performance. I demonstrate that in order to maximize system performance, it is essential to manage the LLCs while being cognizant of its interaction with the system main memory. I propose ReMAP, which reduces the net memory access cost by evicting cache lines that either have no reuse, or have low memory access cost. ReMAP improves the performance of the CMP system by as much as 13%, and by an average of 6.5%. Rather than the LLC, the L1 data cache has a pronounced impact on GPGPU performance by acting as the bandwidth filter for the rest of the memory subsystem. Prior work has shown that the severely constrained data cache capacity in GPGPUs leads to sub-optimal performance. In this thesis, I propose two novel techniques that address the GPGPU data cache capacity problem. I propose ID-Cache that performs effective cache bypassing and cache line size selection to improve cache capacity utilization. Next, I propose LATTE-CC that considers the GPU’s latency tolerance feature and adaptively compresses the data stored in the data cache, thereby increasing its effective capacity. ID-Cache and LATTE-CC are shown to achieve 71% and 19.2% speedup, respectively, over a wide variety of GPGPU applications. Complementing the aforementioned microarchitecture techniques, I identify the need for system architecture innovations to sustain performance scalability of GPG- PUs in the face of slowing Moore’s Law. I propose a novel GPU architecture called the Multi-Chip-Module GPU (MCM-GPU) that integrates multiple GPU modules to form a single logical GPU. With intelligent memory subsystem optimizations tailored for MCM-GPUs, it can achieve within 7% of the performance of a similar but hypothetical monolithic die GPU. Taking a step further, I present an in-depth study of the energy-efficiency characteristics of future MCM-GPUs. I demonstrate that the inherent non-uniform memory access side-effects form the key energy-efficiency bottleneck in the future. In summary, this thesis offers key insights into the performance and energy-efficiency bottlenecks in CMPs and GPGPUs, which can guide future architects towards developing high-performance and energy-efficient general-purpose processors.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Improving Processor Design by Exploiting Performance Variance

Programs exhibit significant performance variance in their access to microarchitectural structures. There are three types of performance variance. First, semantically equivalent programs running on the same system can yield different performance due to characteristics of microarchitectural structures. Second, program phase behavior varies significantly. Third, different types of operations on microarchitectural structure can lead to different performance. In this dissertation, we explore the performance variance and propose techniques to improve the processor design. We explore performance variance caused by microarchitectural structures and propose program interferometry, a technique that perturbs benchmark executables to yield a wide variety of performance points without changing program semantics or other important execution characteristics such as the number of retired instructions. By observing the behavior of the benchmarks over a range of branch prediction accuracies, we can estimate the impact of a microarchitectural optimization optimization and not the rest of the microarchitecture. We explore performance variance caused by phase changes and develop prediction-driven last-level cache (LLC) writeback techniques. We propose a rank idle time prediction driven LLC writeback technique and a last-write prediction driven LLC writeback technique. These techniques improve performance by reducing the write-induced interference. We explore performance variance caused by different types of operations to Non-Volatile Memory (NVM) and propose LLC management policies to reduce write overhead of NVM.We propose an adaptive placement and migration policy for an STT-RAM-based hybrid cache and writeback aware dynamic cache management for NVM-based main memory system. These techniques reduce write latency and write energy, thus leading to performance improvement and energy reduction