ACM TRANSACTIONS ON COMPUTER SYSTEMS (TOCS) 展示了有关计算机系统和系统软件的设计、实施、分析、评估和使用的研究和开发成果。术语“计算机系统”被广泛解释，包括操作系统、系统架构和硬件、分布式系统、优化编译器以及系统和计算机网络之间的交互。出现在 TOCS 中的文章将倾向于介绍新技术和概念，或者报告实际系统的经验和实验。将强调对系统设计者、构建者和用户有用的见解。TOCS 出版研究和技术论文，包括短篇和长篇。它包括技术通信，以允许对技术主题和以前发表的论文进行评论。

ACM Transactions on Computer Systems (TOCS) presents research and development results related to the design, implementation, analysis, evaluation, and use of computer systems and system software. The term 'computer systems' is broadly interpreted to include operating systems, system architecture and hardware, distributed systems, optimizing compilers, and the interactions between systems and computer networks. Articles appearing in TOCS tend to introduce new technologies and concepts or report experiences and experiments from actual systems, emphasizing insights valuable to system designers, builders, and users. TOCS publishes research and technical papers, including both short and long articles, and includes technical communications to allow for commentary on technical topics and previously published papers.

《ACM Transactions on Computer Systems》展示了计算机系统和系统软件的设计、实施、分析、评估和使用方面的研究与开发成果。这里的“计算机系统”涵盖了广泛的领域，包括操作系统、系统架构与硬件、分布式系统、优化编译器，以及系统与计算机网络之间的交互。TOCS 中的文章通常介绍新技术和概念，或报告实际系统的经验和实验，强调对系统设计者、构建者和用户有价值的见解。TOCS 出版研究和技术论文，包括短篇和长篇，同时也包括技术通信，以便对技术主题和之前发表的论文进行评论。

ACM Transactions on Computer Systems

Filesystem fragmentation has been one of the primary reasons for computer systems to get slower over time. However, there have been rapid changes in modern storage systems over the past decades, and modern storage devices such as solid state drives have different mechanisms to access data, compared with traditional rotational ones. In this article, we revisit filesystem fragmentation on modern computer systems from both performance and fairness perspectives. According to our extensive experiments, filesystem fragmentation not only degrades I/O performance of modern storage devices, but also incurs various problems related to I/O fairness, such as performance interference. Unfortunately, conventional defragmentation tools are designed primarily for hard disk drives and thus generate an unnecessarily large amount of I/Os for data migration. To mitigate such problems, this article present FragPicker, a new defragmentation tool for modern storage devices. FragPicker analyzes the I/O behaviors of each target application and defragments only necessary pieces of data whose migration can contribute to performance improvement, thereby effectively minimizing the I/O amount for defragmentation. Our evaluation with YCSB workload-C shows FragPicker reduces the total amount of I/O for defragmentation by around 66% and the elapsed time by around 84%, while showing a similar level of defragmentation effect.

Jonggyu Park

Young Ik Eom

Filesystem Fragmentation on Modern Storage Systems

现代存储系统中的文件系统碎片化

Current technology trends make it possible to build communication networks that can support high-performance distributed computing. This paper describes issues in the design of a prototype switch for an arbitrary topology point-to-point network with link speeds of up to 1 Gbit/s. The switch deals in fixed-length ATM-style cells, which it can process at a rate of 37 million cells per second. It provides high bandwidth and low latency for datagram traffic. In addition, it supports real-time traffic by providing bandwidth reservations with guaranteed latency bounds. The key to the switch's operation is a technique called parallel iterative matching , which can quickly identify a set of conflict-free cells for transmission in a time slot. Bandwidth reservations are accommodated in the switch by building a fixed schedule for transporting cells from reserved flows across the switch; parallel iterative matching can fill unused slots with datagram traffic. Finally, we note that parallel iterative matching may not allocate bandwidth fairly among flows of datagram traffic. We describe a technique called statistical matching , which can be used to ensure fairness at the switch and to support applications with rapidly changing needs for guaranteed bandwidth.

Thomas E. Anderson

Susan S. Owicki

James B. Saxe

Charles P. Thacker

ACM Trans. Comput. Syst.

High-speed switch scheduling for local-area networks

局域网的高速交换调度

Spanner is Google’s scalable, multiversion, globally distributed, and synchronously replicated database. It is the first system to distribute data at global scale and support externally-consistent distributed transactions. This article describes how Spanner is structured, its feature set, the rationale underlying various design decisions, and a novel time API that exposes clock uncertainty. This API and its implementation are critical to supporting external consistency and a variety of powerful features: nonblocking reads in the past, lock-free snapshot transactions, and atomic schema changes, across all of Spanner.

James C. Corbett

Jeffrey Dean

Michael Epstein

Andrew Fikes

Christopher Frost

J. J. Furman

Sanjay Ghemawat

Andrey Gubarev

Christopher Heiser

Peter Hochschild

Wilson Hsieh

Sebastian Kanthak

Eugene Kogan

Hongyi Li

Alexander Lloyd

Sergey Melnik

David Mwaura

David Nagle

Sean Quinlan

Rajesh Rao

Lindsay Rolig

Yasushi Saito

Michal Szymaniak

Christopher Taylor

Ruth Wang

Dale Woodford

Spanner

扳手

Recent GPUs enable Peer-to-Peer Direct Memory Access ( p 2 p ) from fast peripheral devices like NVMe SSDs to exclude the CPU from the data path between them for efficiency. Unfortunately, using p 2 p to access files is challenging because of the subtleties of low-level non-standard interfaces, which bypass the OS file I/O layers and may hurt system performance. Developers must possess intimate knowledge of low-level interfaces to manually handle the subtleties of data consistency and misaligned accesses. We present SPIN , which integrates p 2 p into the standard OS file I/O stack, dynamically activating p 2 p where appropriate, transparently to the user. It combines p 2 p with page cache accesses, re-enables read-ahead for sequential reads, all while maintaining standard POSIX FS consistency, portability across GPUs and SSDs, and compatibility with virtual block devices such as software RAID. We evaluate SPIN on NVIDIA and AMD GPUs using standard file I/O benchmarks, application traces, and end-to-end experiments. SPIN achieves significant performance speedups across a wide range of workloads, exceeding p 2 p throughput by up to an order of magnitude. It also boosts the performance of an aerial imagery rendering application by 2.6× by dynamically adapting to its input-dependent file access pattern, enables 3.3× higher throughput for a GPU-accelerated log server, and enables 29% faster execution for the highly optimized GPU-accelerated image collage with only 30 changed lines of code.

Shai Bergman

Tanya Brokhman

Tzachi Cohen

Mark Silberstein

SPIN

自旋

Cloud computing services often replicate data and may require ways to coordinate distributed actions. Here we present Derecho, a library for such tasks. The API provides interfaces for structuring applications into patterns of subgroups and shards, supports state machine replication within them, and includes mechanisms that assist in restart after failures. Running over 100Gbps RDMA, Derecho can send millions of events per second in each subgroup or shard and throughput peaks at 16GB/s, substantially outperforming prior solutions. Configured to run purely on TCP, Derecho is still substantially faster than comparable widely used, highly-tuned, standard tools. The key insight is that on modern hardware (including non-RDMA networks), data-intensive protocols should be built from non-blocking data-flow components.

Sagar Jha

Jonathan Behrens

Theo Gkountouvas

Mae Milano

Weijia Song

Edward Tremel

Robbert Van Renesse

Sydney Zink

Kenneth P. Birman

Derecho

Persistent memory allocation is a fundamental building block for developing high-performance and in-memory applications. Existing persistent memory allocators suffer from many performance issues. First, they may introduce repeated cache line flushes and small random accesses in persistent memory for their poor heap metadata management. Second, they use static slab segregation resulting in a dramatic increase in memory consumption when allocation request size is changed. Third, they are not aware of NUMA effect, leading to remote persistent memory accesses in memory allocation and deallocation processes. In this article, we design a novel allocator, named PMAlloc, to solve the above issues simultaneously. (1) PMAlloc eliminates cache line reflushes by mapping contiguous data blocks in slabs to interleaved metadata entries stored in different cache lines. (2) It writes small metadata units to a persistent bookkeeping log in a sequential pattern to remove random heap metadata accesses in persistent memory. (3) Instead of using static slab segregation, it supports slab morphing, which allows slabs to be transformed between size classes to significantly improve slab usage. (4) It uses a local-first allocation policy to avoid allocating remote memory blocks. And it supports a two-phase deallocation mechanism including recording and synchronization to minimize the number of remote memory access in the deallocation. PMAlloc is complementary to the existing consistency models. Results on six benchmarks demonstrate that PMAlloc improves the performance of state-of-the-art persistent memory allocators by up to 6.4× and 57× for small and large allocations, respectively. PMAlloc with NUMA optimizations brings a 2.9× speedup in multi-socket evaluation and is up to 36× faster than other persistent memory allocators. Using PMAlloc reduces memory usage by up to 57.8%. Besides, we integrate PMAlloc in a persistent FPTree. Compared to the state-of-the-art allocators, PMAlloc improves the performance of this application by up to 3.1×.

Zheng Dang

Shuibing He

Xuechen Zhang

Peiyi Hong

Zhenxin Li

Xinyu Chen

Haozhe Song

Xian-He Sun

Gang Chen

PMAlloc: A Holistic Approach to Improving Persistent Memory Allocation

PMAlloc：一种改进持久内存分配的整体方法

Boki is a new serverless runtime that exports a shared log API to serverless functions. Boki shared logs enable stateful serverless applications to manage their state with durability, consistency, and fault tolerance. Boki shared logs achieve high throughput and low latency. The key enabler is the metalog , a novel mechanism that allows Boki to address ordering, consistency and fault tolerance independently. The metalog orders shared log records with high throughput and it provides read consistency while allowing service providers to optimize the write and read path of the shared log in different ways. To demonstrate the value of shared logs for stateful serverless applications, we build Boki support libraries that implement fault-tolerant workflows, durable object storage, and message queues. Our evaluation shows that shared logs can speed up important serverless workloads by up to 4.2 ×.

Zhipeng Jia

Emmett Witchel

Boki: Towards Data Consistency and Fault Tolerance with Shared Logs in Stateful Serverless Computing

Boki：在有状态无服务器计算中通过共享日志实现数据一致性和容错

Operating system (OS) is the cornerstone for computer systems. It manages hardware and provides fundamental service for user-level applications. Thus, detecting bugs in OSes is important to improve the reliability of computer systems. Static typestate analysis is a common technique for detecting various types of bugs, but it is often inaccurate or unscalable for large-size OS code, due to imprecision of identifying alias relationships as well as high costs of typestate tracking, path-feasibility validation and inter-procedural analysis.
In this article, we present SPATA, a novel summary-based, alias-aware and path-sensitive typestate analysis framework to detect OS bugs. To identify precise alias relationships in the OS code, SPATA performs a path-based alias analysis based on control-flow paths and access paths. With these alias relationships, SPATA reduces the costs of typestate tracking and path-feasibility validation, to accelerate path-sensitive typestate analysis for accurate bug detection. Moreover, SPATA uses an alias-summary-based analysis to accelerate inter-procedural bug detection, without time-consuming alias analysis across functions. We have evaluated SPATA on the Linux kernel and three popular IoT OSes, and it finds 651 real bugs with a false positive rate of 18%. Besides, our alias-summary-based analysis achieves a 6.7x speedup in bug detection, compared to non-summary-based analysis.

Tuo Li

Jia-Ju Bai

Yulei Sui

Shi-Min Hu

SPATA: Effective OS Bug Detection with Summary-Based, Alias-Aware and Path-Sensitive Typestate Analysis

SPATA：基于摘要、别名感知和路径敏感的类型状态分析实现有效的操作系统缺陷检测

The tiered-memory system can effectively expand the memory capacity for virtual machines (VMs). However, virtualization introduces new challenges specifically in enforcing performance isolation, minimizing context switching, and providing resource overcommit. None of the state-of-the-art designs consider virtualization and address these challenges; we observe that a VM with tiered memory incurs up to a 2× slowdown compared to a DRAM-only VM.
We proposevTMM, a hardware-software collaborative tiered-memory management framework for virtualization. A key insight invTMMis to leverage the unique system features in virtualization to meet the above challenges.vTMMautomatically determines page hotness and migrates pages between fast and slow memory to achieve better performance. Specially,vTMMoptimizes page tracking and migration based on page-modification logging (PML), a hardware-assisted virtualization mechanism, and adaptively distinguishes hot/cold pages through the page “temperature” sorting.vTMMalso dynamically adjusts fast memory among multi-VMs on demand by using a memory pool. Further,vTMMtracks huge pages at regular-page granularity in hardware and splits/merges pages in software, realizing hybrid-grained page management and optimization. We implement and evaluatevTMMwith single-grained page management on an Intel processor, and the hybrid-grained page management on a Sunway processor with hardware mode supporting hardware/software co-designs. Experiments show thatvTMMoutperforms existing tiered-memory management designs in virtualization.

Sai Sha

Chuandong Li

Xiaolin Wang

Zhenlin Wang

Yingwei Luo

Hardware-Software Collaborative Tiered-Memory Management Framework for Virtualization

硬件-软件协同分层内存管理框架用于虚拟化

A common approach to improving resource utilization in data centers is to adaptively provision resources based on the actual workload. One fundamental challenge of doing this in microservice management frameworks, however, is that different components of a service can exhibit significant differences in their impact on end-to-end performance. To make resource management more challenging, a single microservice can be shared by multiple online services that have diverse workload patterns and SLA requirements.
We present an efficient resource management system, namely Erms, for guaranteeing SLAs with high probability in shared microservice environments. Erms profiles microservice latency as a piece-wise linear function of the workload, resource usage, and interference. Based on this profiling, Erms builds resource scaling models to optimally determine latency targets for microservices with complex dependencies. Erms also designs new scheduling policies at shared microservices to further enhance resource efficiency. Experiments across microservice benchmarks as well as trace-driven simulations demonstrate that Erms can reduce SLA violation probability by 5× and more importantly, lead to a reduction in resource usage by 1.6×, compared to state-of-the-art approaches.

Shutian Luo

Chenyu Lin

Kejiang Ye

Guoyao Xu

Liping Zhang

Guodong Yang

Huanle Xu

Chengzhong Xu

Optimizing Resource Management for Shared Microservices: A Scalable System Design

优化共享微服务的资源管理：一种可扩展的系统设计

短名	ACM Trans. Comput. Syst.
Journal Impact	1.82
国际分区	COMPUTER SCIENCE, THEORY & METHODS(Q2)
期刊索引	SCI Q3中科院 4 区

ISSN	0734-2071, 1557-7333
h-index	75
国内分区	计算机科学(4区)计算机科学计算机理论方法(4区)

涉及主题	计算机科学操作系统工程类程序设计语言计算机网络分布式计算数学并行计算电气工程嵌入式系统数据库计算机安全电信经济生物物理计算机硬件
出版信息	出版商: Association for Computing Machinery (ACM)，出版周期: Quarterly，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 1983，原创研究文献占比: 100.00%，自引率:0.00%， Gold OA占比: 0.00%
平均审稿周期	网友分享经验：>12周，或约稿
平均录用比例	网友分享经验：容易

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