Performance and Memory Space Optimizations for Embedded Systems

Embedded systems have three common principles: real-time performance, low power consumption, and low price (limited hardware). Embedded computers use chip multiprocessors (CMPs) to meet these expectations. However, one of the major problems is lack of efficient software support for CMPs; in particular, automated code parallelizers are needed. The aim of this study is to explore various ways to increase performance, as well as reducing resource usage and energy consumption for embedded systems. We use code restructuring, loop scheduling, data transformation, code and data placement, and scratch-pad memory (SPM) management as our tools in different embedded system scenarios. The majority of our work is focused on loop scheduling. Main contributions of our work are: We propose a memory saving strategy that exploits the value locality in array data by storing arrays in a compressed form. Based on the compressed forms of the input arrays, our approach automatically determines the compressed forms of the output arrays and also automatically restructures the code. We propose and evaluate a compiler-directed code scheduling scheme, which considers both parallelism and data locality. It analyzes the code using a locality parallelism graph representation, and assigns the nodes of this graph to processors.We also introduce an Integer Linear Programming based formulation of the scheduling problem. We propose a compiler-based SPM conscious loop scheduling strategy for array/loop based embedded applications. The method is to distribute loop iterations across parallel processors in an SPM-conscious manner. The compiler identifies potential SPM hits and misses, and distributes loop iterations such that the processors have close execution times. We present an SPM management technique using Markov chain based data access. We propose a compiler directed integrated code and data placement scheme for 2-D mesh based CMP architectures. Using a Code-Data Affinity Graph (CDAG) to represent the relationship between loop iterations and array data, it assigns the sets of loop iterations to processing cores and sets of data blocks to on-chip memories. We present a memory bank aware dynamic loop scheduling scheme for array intensive applications.The goal is to minimize the number of memory banks needed for executing the group of loop iterations

Novel online data allocation for hybrid memories on tele-health systems

[EN] The developments of wearable devices such as Body Sensor Networks (BSNs) have greatly improved the capability of tele-health industry. Large amount of data will be collected from every local BSN in real-time. These data is processed by embedded systems including smart phones and tablets. After that, the data will be transferred to distributed storage systems for further processing. Traditional on-chip SRAMs cause critical power leakage issues and occupy relatively large chip areas. Therefore, hybrid memories, which combine volatile memories with non-volatile memories, are widely adopted in reducing the latency and energy cost on multi-core systems. However, most of the current works are about static data allocation for hybrid memories. Those mechanisms cannot achieve better data placement in real-time. Hence, we propose online data allocation for hybrid memories on embedded tele-health systems. In this paper, we present dynamic programming and heuristic approaches. Considering the difference between profiled data access and actual data access, the proposed algorithms use a feedback mechanism to improve the accuracy of data allocation during runtime. Experimental results demonstrate that, compared to greedy approaches, the proposed algorithms achieve 20%-40% performance improvement based on different benchmarks. (C) 2016 Elsevier B.V. All rights reserved.This work is supported by NSF CNS-1457506 and NSF CNS-1359557.Chen, L.; Qiu, M.; Dai, W.; Hassan Mohamed, H. (2017). Novel online data allocation for hybrid memories on tele-health systems. Microprocessors and Microsystems. 52:391-400. https://doi.org/10.1016/j.micpro.2016.08.003S3914005

Piattaforme multicore e integrazione tri-dimensionale: analisi architetturale e ottimizzazione

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.I sistemi integrati moderni sono architetture many-core, in cui spesso lo spazio di memoria è condiviso fra i processori. Per ridurre i consumi, molte di queste architetture sostituiscono le cache dati con memorie scratchpad gestite in software, per massimizzarne la località alle CPU e aumentare le performance. Questo significa che i dati devono essere spostati manualmente da parte del programmatore. Inoltre, tradurre in perfomance l’enorme parallelismo potenziale delle piattaforme many-core non è semplice. Per supportare la programmazione, diversi programming model sono stati proposti, e siccome lavorano ad un alto livello di astrazione, sfruttano delle librerie di runtime che forniscono servizi di base quali sincronizzazione, allocazione della memoria, threading. Queste librerie hanno un costo, che nei sistemi integrati è troppo elevato e ostacola il raggiungimento delle piene performance. Questa tesi analizza come un programming model ad alto livello di astrazione – OpenMP – possa essere efficientemente supportato, se il suo stack software viene adattato per sfruttare al meglio la piattaforma sottostante. In una prima parte, studio diversi meccanismi di sincronizzazione e comunicazione fra thread paralleli, portati sulle piattaforme many-core. In seguito, li utilizzo per scrivere un runtime di supporto a OpenMP che sia il più possibile efficente e “leggero” e che supporti paradigmi di parallelismo multi-livello e irregolare, spesso presenti nelle applicazioni moderne. Una seconda parte della tesi esplora le architetture eterogenee, ossia con acceleratori hardware. Queste architetture soffrono di problematiche sia i) per il processo di design della piattaforma, che ii) di scalabilità della piattaforma stessa (aumento del numero degli acceleratori e dei processori), che iii) di programmabilità. La tesi propone delle soluzioni a tutti e tre i problemi. Il linguaggio di programmazione usato è OpenMP, sia per la sua grande espressività a livello semantico, sia perché è lo standard de-facto per programmare sistemi a memoria condivisa

Evaluator-Executor Transformation for Efficient Conditional Statements on CGRA

Computer EngineeringControl divergence poses many problems in parallelizing loops. While predicated execution is commonly used to convert control dependence into data dependence, it often incurs high overhead because it allocates resources equally for both branches of a conditional statement regardless of their execution frequencies. For those loops with unbalanced conditionals, we propose a software transformation that divides a loop into two or three smaller loops so that the condition is evaluated only in the first loop while the less frequent branch is executed in the second loop in a way that is much more efficient than in the original loop. To reduce the overhead of extra data transfer caused by the loop fission, we also present a hardware extension for a class of coarse-grained reconfigurable architectures (CGRAs). Our experiments using MiBench and computer vision benchmarks on a CGRA demonstrate that our techniques can improve the performance of loops over predicated execution by up to 65%, or 38.0% on average when the hardware extension is enabled. Without any hardware modification, our software-only version can improve performance by up to 64%, or 33.2% on average, while simultaneously reducing the energy consumption of the entire CGRA including configuration and data memory by 22.0% on average.ope

TIME-PREDICTABLE EXECUTION OF EMBEDDED SOFTWARE ON MULTI-CORE PLATFORMS

Ph.DDOCTOR OF PHILOSOPH

Modelli e strumenti di programmazione parallela per piattaforme many-core

The negotiation between power consumption, performance, programmability, and portability drives all computing industry designs, in particular the mobile and embedded systems domains. Two design paradigms have proven particularly promising in this context: architectural heterogeneity and many-core processors. Parallel programming models are key to effectively harness the computational power of heterogeneous many-core SoC. This thesis presents a set of techniques and HW/SW extensions that enable performance improvements and that simplify programmability for heterogeneous many-core platforms. The thesis contributions cover vertically the entire software stack for many-core platforms, from hardware abstraction layers running on top of bare-metal, to programming models; from hardware extensions for efficient parallelism support to middleware that enables optimized resource management within many-core platforms. First, we present mechanisms to decrease parallelism overheads on parallel programming runtimes for many-core platforms, targeting fine-grain parallelism. Second, we present programming model support that enables the offload of computational kernels within heterogeneous many-core systems. Third, we present a novel approach to dynamically sharing and managing many-core platforms when multiple applications coded with different programming models execute concurrently. All these contributions were validated using STMicroelectronics STHORM, a real embodiment of a state-of-the-art many-core system. Hardware extensions and architectural explorations were explored using VirtualSoC, a SystemC based cycle-accurate simulator of many-core platforms

온 칩 네트워크 설계: 매핑, 관리, 라우팅

학위논문 (박사)-- 서울대학교 대학원 : 전기·정보공학부, 2016. 2. 최기영.지난 수십 년간 이어진 반도체 기술의 향상은 매니 코어의 시대를 가져다 주었다. 우리가 일상 생활에 쓰는 데스크톱 컴퓨터조차도 이미 수 개의 코어를 가지고 있으며, 수백 개의 코어를 가진 칩도 상용화되어 있다. 이러한 많은 코어들 간의 통신 기반으로서, 네트워크-온-칩(NoC)이 새로이 대두되었으며, 이는 현재 많은 연구 및 상용 제품에서 널리 사용되고 있다. 그러나 네트워크-온-칩을 매니 코어 시스템에 사용하는 데에는 여러 가지 문제가 따르며, 본 논문에서는 그 중 몇 가지를 풀어내고자 하였다. 본 논문의 두 번째 챕터에서는 NoC 기반 매니코어 구조에 작업을 할당하고 스케쥴하는 방법을 다루었다. 매니코어에의 작업 할당을 다룬 논문은 이미 많이 출판되었지만, 본 연구는 메시지 패싱과 공유 메모리, 두 가지의 통신 방식을 고려함으로써 성능과 에너지 효율을 개선하였다. 또한, 본 연구는 역방향 의존성을 가진 작업 그래프를 스케쥴하는 방법 또한 제시하였다. 3차원 적층 기술은 높아진 전력 밀도 때문에 열 문제가 심각해지는 등, 여러 가지 도전 과제를 내포하고 있다. 세 번째 챕터에서는 DVFS 기술을 이용하여 열 문제를 완화하고자 하는 기술을 소개한다. 각 코어와 라우터가 전압, 작동 속도를 조절할 수 있는 구조에서, 가장 높은 성능을 이끌어 내면서도 최대 온도를 넘어서지 않도록 한다. 세 번째와 네 번째 챕터는 조금 다른 측면을 다룬다. 3D 적층 기술을 사용할 때, 층간 통신은 주로 TSV를 이용하여 이루어진다. 그러나 TSV는 일반 wire보다 훨씬 큰 면적을 차지하기 때문에, 전체 네트워크에서의 TSV 개수는 제한되어야 할 경우가 많다. 이 경우에는 두 가지 선택지가 있는데, 첫째는 각 층간 통신 채널의 대역폭을 줄이는 것이고, 둘째는 각 채널의 대역폭은 유지하되 일부 노드만 층간 통신이 가능한 채널을 제공하는 것이다. 우리는 각각의 경우에 대하여 라우팅 알고리즘을 하나씩 제시한다. 첫 번째 경우에 있어서는 deflection 라우팅 기법을 사용하여 층간 통신의 긴 지연 시간을 극복하고자 하였다. 층간 통신을 균등하게 분배함으로써, 제시된 알고리즘은 개선된 지연 시간을 보이며 라우터 버퍼의 제거를 통한 면적 및 에너지 효율성 또한 얻을 수 있다. 두 번째 경우에서는 층간 통신 채널을 선택하기 위한 몇 가지 규칙을 제시한다. 약간의 라우팅 자유도를 희생함으로써, 제시된 알고리즘은 기존 알고리즘의 가상 채널 요구 조건을 제거하고, 결과적으로는 성능 또는 에너지 효율의 증가를 가져 온다.For decades, advance in semiconductor technology has led us to the era of many-core systems. Today's desktop computers already have multi-core processors, and chips with more than a hundred cores are commercially available. As a communication medium for such a large number of cores, network-on-chip (NoC) has emerged out, and now is being used by many researchers and companies. Adopting NoC for a many-core system incurs many problems, and this thesis tries to solve some of them. The second chapter of this thesis is on mapping and scheduling of tasks on NoC-based CMP architectures. Although mapping on NoC has a number of papers published, our work reveals that selecting communication types between shared memory and message passing can help improve the performance and energy efficiency. Additionally, our framework supports scheduling applications containing backward dependencies with the help of modified modulo scheduling. Evolving the SoCs through 3D stacking makes us face a number of new problems, and the thermal problem coming from increased power density is one of them. In the third chapter of this thesis, we try to mitigate the hotspot problem using DVFS techniques. Assuming that all the routers as well as cores have capabilities to control voltage and frequency individually, we find voltage-frequency pairs for all cores and routers which yields the best performance within the given thermal constraint. The fourth and the fifth chapters of this thesis are from a different aspect. In 3D stacking, inter-layer interconnections are implemented using through-silicon vias (TSV). TSVs usually take much more area than normal wires. Furthermore, they also consume silicon area as well as metal area. For this reason, designers would want to limit the number of TSVs used in their network. To limit the TSV count, there are two options: the first is to reduce the width of each vertical links, and the other is to use fewer vertical links, which results in a partially connected network. We present two routing methodologies for each case. For the network with reduced bandwidth vertical links, we propose using deflection routing to mitigate the long latency of vertical links. By balancing the vertical traffics properly, the algorithm provides improved latency. Also, a large amount of area and energy reduction can be obtained by the removal of router buffers. For partially connected networks, we introduce a set of routing rules for selecting the vertical links. At the expense of sacrificing some amount of routing freedom, the proposed algorithm removes the virtual channel requirement for avoiding deadlock. As a result, the performance, or energy consumption can be reduced at the designer's choice.Chapter 1 Introduction 1 1.1 Task Mapping and Scheduling 2 1.2 Thermal Management 3 1.3 Routing for 3D Networks 5 Chapter 2 Mapping and Scheduling 9 2.1 Introduction 9 2.2 Motivation 10 2.3 Background 12 2.4 Related Work 16 2.5 Platform Description 17 2.5.1 Architcture Description 17 2.5.2 Energy Model 21 2.5.3 Communication Delay Model 22 2.6 Problem Formulation 23 2.7 Proposed Solution 25 2.7.1 Task and Communication Mapping 27 2.7.2 Communication Type Optimization 31 2.7.3 Design Space Pruning via Pre-evaluation 34 2.7.4 Scheduling 35 2.8 Experimental Results 42 2.8.1 Experiments with Coarse-grained Iterative Modulo Scheduling 42 2.8.2 Comparison with Different Mapping Algorithms 43 2.8.3 Experiments with Overall Algorithms 45 2.8.4 Experiments with Various Local Memory Sizes 47 2.8.5 Experiments with Various Placements of Shared Memory 48 Chapter 3 Thermal Management 50 3.1 Introduction 50 3.2 Background 51 3.2.1 Thermal Modeling 51 3.2.2 Heterogeneity in Thermal Propagation 52 3.3 Motivation and Problem Definition 53 3.4 Related Work 56 3.5 Orchestrated Voltage-Frequency Assignment 56 3.5.1 Individual PI Control Method 56 3.5.2 PI Controlled Weighted-Power Budgeting 57 3.5.3 Performance/Power Estimation 59 3.5.4 Frequency Assignment 62 3.5.5 Algorithm Overview 64 3.5.6 Stability Conditions for PI Controller 65 3.6 Experimental Result 66 3.6.1 Experimental Setup 66 3.6.2 Overall Algorithm Performance 68 3.6.3 Accuracy of the Estimation Model 70 3.6.4 Performance of the Frequency Assignment Algorithm 70 Chapter 4 Routing for Limited Bandwidth 3D NoC 72 4.1 Introduction 72 4.2 Motivation 73 4.3 Background 74 4.4 Related Work 75 4.5 3D Deflection Routing 76 4.5.1 Serialized TSV Model 76 4.5.2 TSV Link Injection/ejection Scheme 78 4.5.3 Deadlock Avoidance 80 4.5.4 Livelock Avoidance 84 4.5.5 Router Architecture: Putting It All Together 86 4.5.6 System Level Consideration 87 4.6 Experimental Results 89 4.6.1 Experimental Setup 89 4.6.2 Results on Synthetic Traffic Patterns 91 4.6.3 Results on Realistic Traffic Patterns 94 4.6.4 Results on Real Application Benchmarks 98 4.6.5 Fairness Issue 103 4.6.6 Area Cost Comparison 104 Chapter 5 Routing for Partially Connected 3D NoC 106 5.1 Introduction 106 5.2 Background 107 5.3 Related Work 109 5.4 Proposed Algorithm 111 5.4.1 Preliminary 112 5.4.2 Routing Algorithm for 3-D Stacked Meshes with Regular Partial Vertical Connections 115 5.4.3 Routing Algorithm for 3-D Stacked Meshes with Irregular Partial Vertical Connections 118 5.4.4 Extension to Heterogeneous Mesh Layers 122 5.5 Experimental Results 126 5.5.1 Experimental Setup 126 5.5.2 Experiments on Synthetic Traffics 128 5.5.3 Experiments on Application Benchmarks 133 5.5.4 Comparison with Reduced Bandwidth Mesh 139 Chapter 6 Conclusion 141 Bibliography 144 초록 163Docto

Power management techniques for conserving energy in multiple system components

Energy consumption is a limiting constraint for both embedded and high performance systems. CPU-core, caches and memory contribute a large fraction of energy consumption in most computing systems. As a result, reducing the energy consumption in these components can significantly reduce the system's overall energy consumption. However, applying multiple independent power management policies in the system (one for each component) may interfere with each other and in some occasions increase the combined energy consumption.In this dissertation, I present three power management techniques that target more than a single component in a system. The focus is on reducing the total energy consumption in processors, caches and memory combinations. First, I present a memory-aware processor power management using collaboration between the OS and the compiler. The technique objectives are: (1) finish the application execution before its deadline and (2) minimize the combined energy consumption in processor and memory. Second, I present an Integrated Dynamic Voltage Scaling (IDVS) techniques for processor and on-chip cache power management in multi-voltage domains systems. IDVS co-ordinates power management decisions across voltage domains rather that being applied in isolation in each domain. Third, I present a Power-Aware Cached DRAM (PA-CDRAM) memory organization for reducing the energy consumption in DRAM memory and off-chip caches. PA-CDRAM exploits the high internal memory bandwidth by bringing the off-chip caches "closer" to the memory, which also improves the overall performance.The techniques in my thesis highlight the importance of designing power management schemes that consider multiple components and their interactions (in terms of power and performance) in the system rather than applying multiple isolated power management polices. This study should lay the foundation for further research in the domain of integrated power management, where a single power manager controls many system components