Doctor of Philosophy

dissertationThe computing landscape is undergoing a major change, primarily enabled by ubiquitous wireless networks and the rapid increase in the use of mobile devices which access a web-based information infrastructure. It is expected that most intensive computing may either happen in servers housed in large datacenters (warehouse- scale computers), e.g., cloud computing and other web services, or in many-core high-performance computing (HPC) platforms in scientific labs. It is clear that the primary challenge to scaling such computing systems into the exascale realm is the efficient supply of large amounts of data to hundreds or thousands of compute cores, i.e., building an efficient memory system. Main memory systems are at an inflection point, due to the convergence of several major application and technology trends. Examples include the increasing importance of energy consumption, reduced access stream locality, increasing failure rates, limited pin counts, increasing heterogeneity and complexity, and the diminished importance of cost-per-bit. In light of these trends, the memory system requires a major overhaul. The key to architecting the next generation of memory systems is a combination of the prudent incorporation of novel technologies, and a fundamental rethinking of certain conventional design decisions. In this dissertation, we study every major element of the memory system - the memory chip, the processor-memory channel, the memory access mechanism, and memory reliability, and identify the key bottlenecks to efficiency. Based on this, we propose a novel main memory system with the following innovative features: (i) overfetch-aware re-organized chips, (ii) low-cost silicon photonic memory channels, (iii) largely autonomous memory modules with a packet-based interface to the proces- sor, and (iv) a RAID-based reliability mechanism. Such a system is energy-efficient, high-performance, low-complexity, reliable, and cost-effective, making it ideally suited to meet the requirements of future large-scale computing systems

Doctor of Philosophy in Computing

dissertatio

A Modern Primer on Processing in Memory

Modern computing systems are overwhelmingly designed to move data to computation. This design choice goes directly against at least three key trends in computing that cause performance, scalability and energy bottlenecks: (1) data access is a key bottleneck as many important applications are increasingly data-intensive, and memory bandwidth and energy do not scale well, (2) energy consumption is a key limiter in almost all computing platforms, especially server and mobile systems, (3) data movement, especially off-chip to on-chip, is very expensive in terms of bandwidth, energy and latency, much more so than computation. These trends are especially severely-felt in the data-intensive server and energy-constrained mobile systems of today. At the same time, conventional memory technology is facing many technology scaling challenges in terms of reliability, energy, and performance. As a result, memory system architects are open to organizing memory in different ways and making it more intelligent, at the expense of higher cost. The emergence of 3D-stacked memory plus logic, the adoption of error correcting codes inside the latest DRAM chips, proliferation of different main memory standards and chips, specialized for different purposes (e.g., graphics, low-power, high bandwidth, low latency), and the necessity of designing new solutions to serious reliability and security issues, such as the RowHammer phenomenon, are an evidence of this trend. This chapter discusses recent research that aims to practically enable computation close to data, an approach we call processing-in-memory (PIM). PIM places computation mechanisms in or near where the data is stored (i.e., inside the memory chips, in the logic layer of 3D-stacked memory, or in the memory controllers), so that data movement between the computation units and memory is reduced or eliminated.Comment: arXiv admin note: substantial text overlap with arXiv:1903.0398

DRAM Bender: An Extensible and Versatile FPGA-based Infrastructure to Easily Test State-of-the-art DRAM Chips

To understand and improve DRAM performance, reliability, security and energy efficiency, prior works study characteristics of commodity DRAM chips. Unfortunately, state-of-the-art open source infrastructures capable of conducting such studies are obsolete, poorly supported, or difficult to use, or their inflexibility limit the types of studies they can conduct. We propose DRAM Bender, a new FPGA-based infrastructure that enables experimental studies on state-of-the-art DRAM chips. DRAM Bender offers three key features at the same time. First, DRAM Bender enables directly interfacing with a DRAM chip through its low-level interface. This allows users to issue DRAM commands in arbitrary order and with finer-grained time intervals compared to other open source infrastructures. Second, DRAM Bender exposes easy-to-use C++ and Python programming interfaces, allowing users to quickly and easily develop different types of DRAM experiments. Third, DRAM Bender is easily extensible. The modular design of DRAM Bender allows extending it to (i) support existing and emerging DRAM interfaces, and (ii) run on new commercial or custom FPGA boards with little effort. To demonstrate that DRAM Bender is a versatile infrastructure, we conduct three case studies, two of which lead to new observations about the DRAM RowHammer vulnerability. In particular, we show that data patterns supported by DRAM Bender uncovers a larger set of bit-flips on a victim row compared to the data patterns commonly used by prior work. We demonstrate the extensibility of DRAM Bender by implementing it on five different FPGAs with DDR4 and DDR3 support. DRAM Bender is freely and openly available at https://github.com/CMU-SAFARI/DRAM-Bender.Comment: To appear in TCAD 202

성능과 용량 향상을 위한 적층형 메모리 구조

학위논문 (박사)-- 서울대학교 대학원 : 융합과학기술대학원 융합과학부(지능형융합시스템전공), 2019. 2. 안정호.The advance of DRAM manufacturing technology slows down, whereas the density and performance needs of DRAM continue to increase. This desire has motivated the industry to explore emerging Non-Volatile Memory (e.g., 3D XPoint) and the high-density DRAM (e.g., Managed DRAM Solution). Since such memory technologies increase the density at the cost of longer latency, lower bandwidth, or both, it is essential to use them with fast memory (e.g., conventional DRAM) to which hot pages are transferred at runtime. Nonetheless, we observe that page transfers to fast memory often block memory channels from servicing memory requests from applications for a long period. This in turn significantly increases the high-percentile response time of latency-sensitive applications. In this thesis, we propose a high-density managed DRAM architecture, dubbed 3D-XPath for applications demanding both low latency and high capacity for memory. 3D-XPath DRAM stacks conventional DRAM dies with high-density DRAM dies explored in this thesis and connects these DRAM dies with 3D-XPath. Especially, 3D-XPath allows unused memory channels to service memory requests from applications when primary channels supposed to handle the memory requests are blocked by page transfers at given moments, considerably increasing the high-percentile response time. This can also improve the throughput of applications frequently copying memory blocks between kernel and user memory spaces. Our evaluation shows that 3D-XPath DRAM decreases high-percentile response time of latency-sensitive applications by ∼30% while improving the throughput of an I/O-intensive applications by ∼39%, compared with DRAM without 3D-XPath. Recent computer systems are evolving toward the integration of more CPU cores into a single socket, which require higher memory bandwidth and capacity. Increasing the number of channels per socket is a common solution to the bandwidth demand and to better utilize these increased channels, data bus width is reduced and burst length is increased. However, this longer burst length brings increased DRAM access latency. On the memory capacity side, process scaling has been the answer for decades, but cell capacitance now limits how small a cell could be. 3D stacked memory solves this problem by stacking dies on top of other dies. We made a key observation in real multicore machine that multiple memory controllers are always not fully utilized on SPEC CPU 2006 rate benchmark. To bring these idle channels into play, we proposed memory channel sharing architecture to boost peak bandwidth of one memory channel and reduce the burst latency on 3D stacked memory. By channel sharing, the total performance on multi-programmed workloads and multi-threaded workloads improved up to respectively 4.3% and 3.6% and the average read latency reduced up to 8.22% and 10.18%.DRAM 제조 기술의 발전은 속도가 느려지는 반면 DRAM의 밀도 및 성능 요구는 계속 증가하고 있다. 이러한 요구로 인해 새로운 비 휘발성 메모리(예: 3D-XPoint) 및 고밀도 DRAM(예: Managed asymmetric latency DRAM Solution)이 등장하였다. 이러한 고밀도 메모리 기술은 긴 레이턴시, 낮은 대역폭 또는 두 가지 모두를 사용하는 방식으로 밀도를 증가시키기 때문에 성능이 좋지 않아, 핫 페이지를 고속 메모리(예: 일반 DRAM)로 스왑되는 저용량의 고속 메모리가 동시에 사용되는 것이 일반적이다. 이러한 스왑 과정에서 빠른 메모리로의 페이지 전송이 일반적인 응용프로그램의 메모리 요청을 오랫동안 처리하지 못하도록 하기 때문에, 대기 시간에 민감한 응용 프로그램의 백분위 응답 시간을 크게 증가시켜, 응답 시간의 표준 편차를 증가시킨다. 이러한 문제를 해결하기 위해 본 학위 논문에서는 저 지연시간 및 고용량 메모리를 요구하는 애플리케이션을 위해 3D-XPath, 즉 고밀도 관리 DRAM 아키텍처를 제안한다. 이러한 3D-톔소를 집적한 DRAM은 저속의 고밀도 DRAM 다이를 기존의 일반적인 DRAM 다이와 동시에 한 칩에 적층하고, DRAM 다이끼리는 제안하는 3D-XPath 하드웨어를 통해 연결된다. 이러한 3D-XPath는 핫 페이지 스왑이 일어나는 동안 응용프로그램의 메모리 요청을 차단하지 않고 사용량이 적은 메모리 채널로 핫 페이지 스왑을 처리 할 수 있도록 하여, 데이터 집중 응용 프로그램의 백분위 응답 시간을 개선시킨다. 또한 제안하는 하드웨어 구조를 사용하여, 추가적으로 O/S 커널과 유저 스페이스 간의 메모리 블록을 자주 복사하는 응용 프로그램의 처리량을 향상시킬 수 있다. 이러한 3D-XPath DRAM은 3D-XPath가 없는 DRAM에 비해 I/O 집약적인 응용프로그램의 처리량을 최대 39 % 향상시키면서 레이턴시에 민감한 응용 프로그램의 높은 백분위 응답 시간을 최대 30 %까지 감소시킬 수 있다. 또한 최근의 컴퓨터 시스템은 보다 많은 메모리 대역폭과 용량을 필요로하는 더 많은 CPU 코어를 단일 소켓으로 통합하는 방향으로 진화하고 있다. 이러한 소켓 당 채널 수를 늘리는 것은 대역폭 요구에 대한 일반적인 해결책이며, 최신의 DRAM 인터페이스의 발전 양상은 증가한 채널을 보다 잘 활용하기 위해 데이터 버스 폭이 감소되고 버스트 길이가 증가한다. 그러나 길어진 버스트 길이는 DRAM 액세스 대기 시간을 증가시킨다. 추가적으로 최신의 응용프로그램은 더 많은 메모리 용량을 요구하며, 미세 공정으로 메모리 용량을 증가시키는 방법론은 수십 년 동안 사용되었지만, 20 nm 이하의 미세공정에서는 더 이상 공정 미세화를 통해 메모리 밀도를 증가시키기가 어려운 상황이며, 적층형 메모리를 사용하여 용량을 증가시키는 방법을 사용한다. 이러한 상황에서, 실제 최신의 멀티코어 머신에서 SPEC CPU 2006 응용프로그램을 멀티코어에서 실행하였을 때, 항상 시스템의 모든 메모리 컨트롤러가 완전히 활용되지 않는다는 사실을 관찰했다. 이러한 유휴 채널을 사용하기 위해 하나의 메모리 채널의 피크 대역폭을 높이고 3D 스택 메모리의 버스트 대기 시간을 줄이기 위해 본 학위 논문에서는 메모리 채널 공유 아키텍처를 제안하였으며, 하드웨어 블록을 제안하였다. 이러한 채널 공유를 통해 멀티 프로그램 된 응용프로그램 및 다중 스레드 응용프로그램 성능이 각각 4.3 % 및 3.6 %로 향상되었으며 평균 읽기 대기 시간은 8.22 % 및 10.18 %로 감소하였다.Contents Abstract i Contents iv List of Figures vi List of Tables viii Introduction 1 1.1 3D-XPath: High-Density Managed DRAM Architecture with Cost-effective Alternative Paths for Memory Transactions 5 1.2 Boosting Bandwidth – Dynamic Channel Sharing on 3D Stacked Memory 9 1.3 Research contribution 13 1.4 Outline 14 3D-stacked Heterogeneous Memory Architecture with Cost-effective Extra Block Transfer Paths 17 2.1 Background 17 2.1.1 Heterogeneous Main Memory Systems 17 2.1.2 Specialized DRAM 19 2.1.3 3D-stacked Memory 22 2.2 HIGH-DENSITY DRAM ARCHITECTURE 27 2.2.1 Key Design Challenges 29 2.2.2 Plausible High-density DRAM Designs 33 2.3 3D-STACKED DRAM WITH ALTERNATIVE PATHS FOR MEMORY TRANSACTIONS 37 2.3.1 3D-XPath Architecture 41 2.3.2 3D-XPath Management 46 2.4 EXPERIMENTAL METHODOLOGY 52 2.5 EVALUATION 56 2.5.1 OLDI Workloads 56 2.5.2 Non-OLDI Workloads 61 2.5.3 Sensitivity Analysis 66 2.6 RELATED WORK 70 Boosting bandwidth –Dynamic Channel Sharing on 3D Stacked Memory 72 3.1 Background: Memory Operations 72 3.1.1. Memory Controller 72 3.1.2 DRAM column access sequence 73 3.2 Related Work 74 3.3. CHANNEL SHARING ENABLED MEMORY SYSTEM 76 3.3.1 Hardware Requirements 78 3.3.2 Operation Sequence 81 3.4 Analysis 87 3.4.1 Experiment Environment 87 3.4.2 Performance 88 3.4.3 Overhead 90 CONCLUSION 92 REFERENCES 94 국문초록 107Docto