arXiv - CS - Operating Systems最新文献_第2页

Wave: A Split OS Architecture for Application Engines 波浪应用引擎的分离式操作系统架构

arXiv - CS - Operating Systems Pub Date : 2024-08-30 DOI: arxiv-2408.17351

Jack Tigar Humphries, Neel Natu, Kostis Kaffes, Stanko Novaković, Paul Turner, Hank Levy, David Culler, Christos Kozyrakis

{"title":"Wave: A Split OS Architecture for Application Engines","authors":"Jack Tigar Humphries, Neel Natu, Kostis Kaffes, Stanko Novaković, Paul Turner, Hank Levy, David Culler, Christos Kozyrakis","doi":"arxiv-2408.17351","DOIUrl":"https://doi.org/arxiv-2408.17351","url":null,"abstract":"The end of Moore's Law and the tightening performance requirements in today's\u0000clouds make re-architecting the software stack a necessity. To address this,\u0000cloud providers and vendors offload the virtualization control plane and data\u0000plane, along with the host OS data plane, to IPUs (SmartNICs), recovering\u0000scarce host resources that are then used by applications. However, the host OS\u0000control plane--encompassing kernel thread scheduling, memory management, the\u0000network stack, file systems, and more--is left on the host CPU and degrades\u0000workload performance. This paper presents Wave, a split OS architecture that moves OS subsystem\u0000policies to the IPU while keeping OS mechanisms on the host CPU. Wave not only\u0000frees host CPU resources, but it reduces host workload interference and\u0000leverages network insights on the IPU to improve policy decisions. Wave makes\u0000OS control plane offloading practical despite high host-IPU communication\u0000latency, lack of a coherent interconnect, and operation across two system\u0000images. We present Wave's design and implementation, and implement several OS\u0000subsystems in Wave, including kernel thread scheduling, the control plane for a\u0000network stack, and memory management. We then evaluate the Wave subsystems on\u0000Stubby (scheduling and network), our GCE VM service (scheduling), and RocksDB\u0000(memory management and scheduling). We demonstrate that Wave subsystems are\u0000competitive with and often superior to on-host subsystems, saving 8 host CPUs\u0000for Stubby, 16 host CPUs for database memory management, and improving VM\u0000performance by up to 11.2%.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FRAP: A Flexible Resource Accessing Protocol for Multiprocessor Real-Time Systems FRAP：多处理器实时系统的灵活资源访问协议

arXiv - CS - Operating Systems Pub Date : 2024-08-25 DOI: arxiv-2408.13772

Shuai Zhao, Hanzhi Xu, Nan Chen, Ruoxian Su, Wanli Chang

{"title":"FRAP: A Flexible Resource Accessing Protocol for Multiprocessor Real-Time Systems","authors":"Shuai Zhao, Hanzhi Xu, Nan Chen, Ruoxian Su, Wanli Chang","doi":"arxiv-2408.13772","DOIUrl":"https://doi.org/arxiv-2408.13772","url":null,"abstract":"Fully-partitioned fixed-priority scheduling (FP-FPS) multiprocessor systems\u0000are widely found in real-time applications, where spin-based protocols are\u0000often deployed to manage the mutually exclusive access of shared resources.\u0000Unfortunately, existing approaches either enforce rigid spin priority rules for\u0000resource accessing or carry significant pessimism in the schedulability\u0000analysis, imposing substantial blocking time regardless of task execution\u0000urgency or resource over-provisioning. This paper proposes FRAP, a spin-based\u0000flexible resource accessing protocol for FP-FPS systems. A task under FRAP can\u0000spin at any priority within a range for accessing a resource, allowing flexible\u0000and fine-grained resource control with predictable worst-case behaviour. Under\u0000flexible spinning, we demonstrate that the existing analysis techniques can\u0000lead to incorrect timing bounds and present a novel MCMF (minimum cost maximum\u0000flow)-based blocking analysis, providing predictability guarantee for FRAP. A\u0000spin priority assignment is reported that fully exploits flexible spinning to\u0000reduce the blocking time of tasks with high urgency, enhancing the performance\u0000of FRAP. Experimental results show that FRAP outperforms the existing\u0000spin-based protocols in schedulability by 15.20%-32.73% on average, up to\u000065.85%.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Telepathic Datacenters: Fast RPCs using Shared CXL Memory 远程数据中心：使用共享 CXL 内存实现快速 RPC

arXiv - CS - Operating Systems Pub Date : 2024-08-21 DOI: arxiv-2408.11325

Suyash Mahar, Ehsan Hajyjasini, Seungjin Lee, Zifeng Zhang, Mingyao Shen, Steven Swanson

{"title":"Telepathic Datacenters: Fast RPCs using Shared CXL Memory","authors":"Suyash Mahar, Ehsan Hajyjasini, Seungjin Lee, Zifeng Zhang, Mingyao Shen, Steven Swanson","doi":"arxiv-2408.11325","DOIUrl":"https://doi.org/arxiv-2408.11325","url":null,"abstract":"Datacenter applications often rely on remote procedure calls (RPCs) for fast,\u0000efficient, and secure communication. However, RPCs are slow, inefficient, and\u0000hard to use as they require expensive serialization and compression to\u0000communicate over a packetized serial network link. Compute Express Link 3.0\u0000(CXL) offers an alternative solution, allowing applications to share data using\u0000a cache-coherent, shared-memory interface across clusters of machines. RPCool is a new framework that exploits CXL's shared memory capabilities.\u0000RPCool avoids serialization by passing pointers to data structures in shared\u0000memory. While avoiding serialization is useful, directly sharing pointer-rich\u0000data eliminates the isolation that copying data over traditional networks\u0000provides, leaving the receiver vulnerable to invalid pointers and concurrent\u0000updates to shared data by the sender. RPCool restores this safety with careful\u0000and efficient management of memory permissions. Another significant challenge\u0000with CXL shared memory capabilities is that they are unlikely to scale to an\u0000entire datacenter. RPCool addresses this by falling back to RDMA-based\u0000communication. Overall, RPCool reduces the round-trip latency by 1.93$times$ and\u00007.2$times$ compared to state-of-the-art RDMA and CXL-based RPC mechanisms,\u0000respectively. Moreover, RPCool performs either comparably or better than other\u0000RPC mechanisms across a range of workloads.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CRISP: Confidentiality, Rollback, and Integrity Storage Protection for Confidential Cloud-Native Computing CRISP：为机密云原生计算提供机密性、回滚和完整性存储保护

arXiv - CS - Operating Systems Pub Date : 2024-08-13 DOI: arxiv-2408.06822

Ardhi Putra Pratama Hartono, Andrey Brito, Christof Fetzer

引用次数: 0

Wasm-bpf: Streamlining eBPF Deployment in Cloud Environments with WebAssembly Wasm-bpf：利用 WebAssembly 简化云环境中的 eBPF 部署

arXiv - CS - Operating Systems Pub Date : 2024-08-09 DOI: arxiv-2408.04856

Yusheng Zheng, Tong Yu, Yiwei Yang, Andrew Quinn

{"title":"Wasm-bpf: Streamlining eBPF Deployment in Cloud Environments with WebAssembly","authors":"Yusheng Zheng, Tong Yu, Yiwei Yang, Andrew Quinn","doi":"arxiv-2408.04856","DOIUrl":"https://doi.org/arxiv-2408.04856","url":null,"abstract":"The extended Berkeley Packet Filter (eBPF) is extensively utilized for\u0000observability and performance analysis in cloud-native environments. However,\u0000deploying eBPF programs across a heterogeneous cloud environment presents\u0000challenges, including compatibility issues across different kernel versions,\u0000operating systems, runtimes, and architectures. Traditional deployment methods,\u0000such as standalone containers or tightly integrated core applications, are\u0000cumbersome and inefficient, particularly when dynamic plugin management is\u0000required. To address these challenges, we introduce Wasm-bpf, a lightweight\u0000runtime on WebAssembly and the WebAssembly System Interface (WASI). Leveraging\u0000Wasm platform independence and WASI standardized system interface, with\u0000enhanced relocation for different architectures, Wasm-bpf ensures\u0000cross-platform compatibility for eBPF programs. It simplifies deployment by\u0000integrating with container toolchains, allowing eBPF programs to be packaged as\u0000Wasm modules that can be easily managed within cloud environments.\u0000Additionally, Wasm-bpf supports dynamic plugin management in WebAssembly. Our\u0000implementation and evaluation demonstrate that Wasm-bpf introduces minimal\u0000overhead compared to native eBPF implementations while simplifying the\u0000deployment process.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141930974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Crash Consistency in DRAM-NVM-Disk Hybrid Storage System DRAM-NVM-Disk 混合存储系统的碰撞一致性

arXiv - CS - Operating Systems Pub Date : 2024-08-08 DOI: arxiv-2408.04238

Guoyu Wang, Xilong Che, Haoyang Wei, Chenju Pei, Juncheng Hu

引用次数: 0

Hardware-Assisted Virtualization of Neural Processing Units for Cloud Platforms 云平台神经处理单元的硬件辅助虚拟化

arXiv - CS - Operating Systems Pub Date : 2024-08-07 DOI: arxiv-2408.04104

Yuqi Xue, Yiqi Liu, Lifeng Nai, Jian Huang

{"title":"Hardware-Assisted Virtualization of Neural Processing Units for Cloud Platforms","authors":"Yuqi Xue, Yiqi Liu, Lifeng Nai, Jian Huang","doi":"arxiv-2408.04104","DOIUrl":"https://doi.org/arxiv-2408.04104","url":null,"abstract":"Cloud platforms today have been deploying hardware accelerators like neural\u0000processing units (NPUs) for powering machine learning (ML) inference services.\u0000To maximize the resource utilization while ensuring reasonable quality of\u0000service, a natural approach is to virtualize NPUs for efficient resource\u0000sharing for multi-tenant ML services. However, virtualizing NPUs for modern\u0000cloud platforms is not easy. This is not only due to the lack of system\u0000abstraction support for NPU hardware, but also due to the lack of architectural\u0000and ISA support for enabling fine-grained dynamic operator scheduling for\u0000virtualized NPUs. We present TCloud, a holistic NPU virtualization framework. We investigate\u0000virtualization techniques for NPUs across the entire software and hardware\u0000stack. TCloud consists of (1) a flexible NPU abstraction called vNPU, which\u0000enables fine-grained virtualization of the heterogeneous compute units in a\u0000physical NPU (pNPU); (2) a vNPU resource allocator that enables pay-as-you-go\u0000computing model and flexible vNPU-to-pNPU mappings for improved resource\u0000utilization and cost-effectiveness; (3) an ISA extension of modern NPU\u0000architecture for facilitating fine-grained tensor operator scheduling for\u0000multiple vNPUs. We implement TCloud based on a production-level NPU simulator.\u0000Our experiments show that TCloud improves the throughput of ML inference\u0000services by up to 1.4$times$ and reduces the tail latency by up to\u00004.6$times$, while improving the NPU utilization by 1.2$times$ on average,\u0000compared to state-of-the-art NPU sharing approaches.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"105 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141930973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NVPC: A Transparent NVM Page Cache NVPC：透明的 NVM 页面缓存

arXiv - CS - Operating Systems Pub Date : 2024-08-06 DOI: arxiv-2408.02911

Guoyu Wang, Xilong Che, Haoyang Wei, Shuo Chen, Puyi He, Juncheng Hu

{"title":"NVPC: A Transparent NVM Page Cache","authors":"Guoyu Wang, Xilong Che, Haoyang Wei, Shuo Chen, Puyi He, Juncheng Hu","doi":"arxiv-2408.02911","DOIUrl":"https://doi.org/arxiv-2408.02911","url":null,"abstract":"Towards a compatible utilization of NVM, NVM-specialized kernel file systems\u0000and NVM-based disk file system accelerators have been proposed. However, these\u0000studies only focus on one or several characteristics of NVM, while failing to\u0000exploit its best practice by putting NVM in the proper position of the whole\u0000storage stack. In this paper, we present NVPC, a transparent acceleration to\u0000existing kernel file systems with an NVM-enhanced page cache. The acceleration\u0000lies in two aspects, respectively matching the desperate needs of existing disk\u0000file systems: sync writes and cache-missed operations. Besides, the fast DRAM\u0000page cache is preserved for cache-hit operations. For sync writes, a\u0000high-performance log-based sync absorbing area is provided to redirect data\u0000destination from the slow disk to the fast NVM. Meanwhile, the byte-addressable\u0000feature of NVM is used to prevent write amplification. For cache-missed\u0000operations, NVPC makes use of the idle space on NVM to extend the DRAM page\u0000cache, so that more and larger workloads can fit into the cache. NVPC is\u0000entirely implemented as a page cache, thus can provide efficient speed-up to\u0000disk file systems with full transparency to users and full compatibility to\u0000lower file systems. In Filebench macro-benchmarks, NVPC achieves at most 3.55x, 2.84x, and 2.64x\u0000faster than NOVA, Ext-4, and SPFS. In RocksDB workloads with working set larger\u0000than DRAM, NVPC achieves 1.12x, 2.59x, and 2.11x faster than NOVA, Ext-4, and\u0000SPFS. Meanwhile, NVPC gains positive revenue from NOVA, Ext-4, and SPFS in\u000062.5% of the tested cases in our read/write/sync mixed evaluation,\u0000demonstrating that NVPC is more balanced and adaptive to complex real-world\u0000workloads. Experimental results also show that NVPC is the only method that\u0000accelerates Ext-4 in particular cases for up to 15.19x, with no slow-down to\u0000any other use cases.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Operating System And Artificial Intelligence: A Systematic Review 操作系统与人工智能：系统回顾

arXiv - CS - Operating Systems Pub Date : 2024-07-19 DOI: arxiv-2407.14567

Yifan Zhang, Xinkui Zhao, Jianwei Yin, Lufei Zhang, Zuoning Chen

{"title":"Operating System And Artificial Intelligence: A Systematic Review","authors":"Yifan Zhang, Xinkui Zhao, Jianwei Yin, Lufei Zhang, Zuoning Chen","doi":"arxiv-2407.14567","DOIUrl":"https://doi.org/arxiv-2407.14567","url":null,"abstract":"In the dynamic landscape of technology, the convergence of Artificial\u0000Intelligence (AI) and Operating Systems (OS) has emerged as a pivotal arena for\u0000innovation. Our exploration focuses on the symbiotic relationship between AI\u0000and OS, emphasizing how AI-driven tools enhance OS performance, security, and\u0000efficiency, while OS advancements facilitate more sophisticated AI\u0000applications. We delve into various AI techniques employed to optimize OS\u0000functionalities, including memory management, process scheduling, and intrusion\u0000detection. Simultaneously, we analyze the role of OS in providing essential\u0000services and infrastructure that enable effective AI application execution,\u0000from resource allocation to data processing. The article also addresses\u0000challenges and future directions in this domain, emphasizing the imperative of\u0000secure and efficient AI integration within OS frameworks. By examining case\u0000studies and recent developments, our review provides a comprehensive overview\u0000of the current state of AI-OS integration, underscoring its significance in\u0000shaping the next generation of computing technologies. Finally, we explore the\u0000promising prospects of Intelligent OSes, considering not only how innovative OS\u0000architectures will pave the way for groundbreaking opportunities but also how\u0000AI will significantly contribute to advancing these next-generation OSs.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven Software-based Power Estimation for Embedded Devices 基于数据驱动软件的嵌入式设备功耗估算

arXiv - CS - Operating Systems Pub Date : 2024-07-03 DOI: arxiv-2407.02764

Haoyu Wang, Xinyi Li, Ti Zhou, Man Lin

{"title":"Data-driven Software-based Power Estimation for Embedded Devices","authors":"Haoyu Wang, Xinyi Li, Ti Zhou, Man Lin","doi":"arxiv-2407.02764","DOIUrl":"https://doi.org/arxiv-2407.02764","url":null,"abstract":"Energy measurement of computer devices, which are widely used in the Internet\u0000of Things (IoT), is an important yet challenging task. Most of these IoT\u0000devices lack ready-to-use hardware or software for power measurement. A\u0000cost-effective solution is to use low-end consumer-grade power meters. However,\u0000these low-end power meters cannot provide accurate instantaneous power\u0000measurements. In this paper, we propose an easy-to-use approach to derive an\u0000instantaneous software-based energy estimation model with only low-end power\u0000meters based on data-driven analysis through machine learning. Our solution is\u0000demonstrated with a Jetson Nano board and Ruideng UM25C USB power meter.\u0000Various machine learning methods combined with our smart data collection method\u0000and physical measurement are explored. Benchmarks were used to evaluate the\u0000derived software-power model for the Jetson Nano board and Raspberry Pi. The\u0000results show that 92% accuracy can be achieved compared to the long-duration\u0000measurement. A kernel module that can collect running traces of utilization and\u0000frequencies needed is developed, together with the power model derived, for\u0000power prediction for programs running in real environment.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0