Paper abstracts and proceedings front matter are available to everyone now. 2019 - Present. We introduce a hybrid cryptographic protocol for privacy-adhering transformations of encrypted data. Across a wide range of pages, phones, and mobile networks covering web workloads in both developed and emerging regions, Horcrux reduces median browser computation delays by 31-44% and page load times by 18-37%. Web pages today commonly include large amounts of JavaScript code in order to offer users a dynamic experience. In contrast, CLP achieves significantly higher compression ratio than all commonly used compressors, yet delivers fast search performance that is comparable or even better than Elasticsearch and Splunk Enterprise. Prior or concurrent workshop publication does not preclude publishing a related paper in OSDI. Our evaluation shows that PET outperforms existing systems by up to 2.5, by unlocking previously missed opportunities from partially equivalent transformations. It then feeds those invariants and the desired safety properties to an SMT solver to check if the conjunction of the invariants and the safety properties is inductive. OSDI'20: 14th USENIX Conference on Operating Systems Design and ImplementationNovember 4 - 6, 2020 ISBN: 978-1-939133-19-9 Published: 04 November 2020 Sponsors: ORACLE, VMware, Google Inc., Amazon, Microsoft Get Alerts for this Conference Save to Binder Export Citation Bibliometrics Citation count 96 Downloads (6 weeks) 317 Downloads (12 months) Academic and industrial participants present research and experience papers that cover the full range of theory . CLP's gains come from using a tuned, domain-specific compression and search algorithm that exploits the significant amount of repetition in text logs. The NAL maintains 1) per-node partial views in PM for serving insert/update/delete operations with failure atomicity and 2) a global view in DRAM for serving lookup operations. Session Chairs: Moshe Gabel, University of Toronto, and Joseph Gonzalez, University of California, Berkeley, John Thorpe, Yifan Qiao, Jonathan Eyolfson, and Shen Teng, UCLA; Guanzhou Hu, UCLA and University of Wisconsin, Madison; Zhihao Jia, CMU; Jinliang Wei, Google Brain; Keval Vora, Simon Fraser; Ravi Netravali, Princeton University; Miryung Kim and Guoqing Harry Xu, UCLA. Consensus bugs are bugs that make Ethereum clients transition to incorrect blockchain states and fail to reach consensus with other clients. The experimental results show that Penglai can support 1,000s enclave instances running concurrently and scale up to 512GB secure memory with both encryption and integrity protection. Our approach effectively eliminates high communication and partitioning overheads, and couples it with a new pipelined push-pull parallelism based execution strategy for fast model training. Submission of a response is optional. Starting with small invariant formulas and strongest possible invariants avoids large SMT queries, improving SMT solver performance. Second, it innovates on the underlying cryptographic machinery and constructs a new private information retrieval scheme, FastPIR, that reduces the time to process oblivious access requests for mailboxes. Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, and Yufei Ding, University of California, Santa Barbara. Nico Lehmann and Rose Kunkel, UC San Diego; Jordan Brown, Independent; Jean Yang, Akita Software; Niki Vazou, IMDEA Software Institute; Nadia Polikarpova, Deian Stefan, and Ranjit Jhala, UC San Diego. However, with the increasingly speedy transactions and queries thanks to large memory and fast interconnect, commodity HTAP systems have to make a tradeoff between data freshness and performance degradation. This paper presents the design and implementation of CLP, a tool capable of losslessly compressing unstructured text logs while enabling fast searches directly on the compressed data. We present the results of a 1% experiment at fleet scale as well as the longitudinal rollout in Googles warehouse scale computers. All deadline times are 23:59 hrs UTC. We present the nanoPU, a new NIC-CPU co-design to accelerate an increasingly pervasive class of datacenter applications: those that utilize many small Remote Procedure Calls (RPCs) with very short (s-scale) processing times. Poor data locality hurts an application's performance. This motivates the need for a new approach to data privacy that can provide strong assurance and control to users. USENIX discourages program co-chairs from submitting papers to the conferences they organize, although they are allowed to do so. Devices employ adaptive interrupt coalescing heuristics that try to balance between these opposing goals. Our evaluation shows that, compared to existing participant selection mechanisms, Oort improves time-to-accuracy performance by 1.2X-14.1X and final model accuracy by 1.3%-9.8%, while efficiently enforcing developer-specified model testing criteria at the scale of millions of clients. Second, Fluffy uses multiple existing Ethereum clients that independently implement the specification as cross-referencing oracles. Session Chairs: Gennady Pekhimenko, University of Toronto / Vector Institute, and Shivaram Venkataraman, University of WisconsinMadison, Aurick Qiao, Petuum, Inc. and Carnegie Mellon University; Sang Keun Choe and Suhas Jayaram Subramanya, Carnegie Mellon University; Willie Neiswanger, Petuum, Inc. and Carnegie Mellon University; Qirong Ho, Petuum, Inc.; Hao Zhang, Petuum, Inc. and UC Berkeley; Gregory R. Ganger, Carnegie Mellon University; Eric P. Xing, MBZUAI, Petuum, Inc., and Carnegie Mellon University. We discuss the design and implementation of TEMERAIRE including strategies for hugepage-aware memory layouts to maximize hugepage coverage and to minimize fragmentation overheads. GoJournal is implemented in Go, and Perennial is implemented in the Coq proof assistant. Reviews will be available for response on Wednesday, March 3, 2021. Responses should be limited to clarifying the submitted work. Mothy received a PhD in 1995 from the Computer Laboratory of the University of Cambridge, where he was a principal designer and builder of the Nemesis OS. We demonstrate the above using design, implementation and evaluation of blk-switch, a new Linux kernel storage stack architecture. The papers will be available online to everyone beginning on the first day of the conference, July 14, 2021. To this end, we propose GNNAdvisor, an adaptive and efficient runtime system to accelerate various GNN workloads on GPU platforms. Hence, kernel developers are constantly refining synchronization within OS kernels to improve scalability at the risk of introducing subtle bugs. For instance, FAST 21 and NSDI 21 have author-notification dates after the OSDI 21 abstract-registration deadline. Grand Rapids, Michigan, United States . USENIX NSDI, 2021 Acceptance Rate: 15.99% Fluid: Resource-Aware Hyperparameter Tuning Engine P. Yu*, J. Liu*, M. Chowdhury (*Equal contribution) MLSys, 2021 Acceptance Rate: 23.53% NetLock: Fast, Centralized Lock Management Using Programmable Switches Z. Yu, Y. Zhang, V. Braverman, M. Chowdhury, X. Jin ACM SIGCOMM, 2020 Acceptance Rate: 21.6% If you have any questions about conflicts, please contact the program co-chairs. blk-switch evaluation over a variety of scenarios shows that it consistently achieves s-scale average and tail latency (at both 99th and 99.9th percentiles), while allowing applications to near-perfectly utilize the hardware capacity. Qing Wang, Youyou Lu, Junru Li, and Jiwu Shu, Tsinghua University. Lukas Burkhalter, Nicolas Kchler, Alexander Viand, Hossein Shafagh, and Anwar Hithnawi, ETH Zrich. All submissions will be treated as confidential prior to publication on the USENIX OSDI 21 website; rejected submissions will be permanently treated as confidential. This change is receiving considerable attention in the architecture and security communities, for example, but in contrast, so-called OS researchers are mostly in denial. For general conference information, see https://www.usenix.org/conference/osdi22. Kyuhwa Han, Sungkyunkwan University and Samsung Electronics; Hyunho Gwak and Dongkun Shin, Sungkyunkwan University; Jooyoung Hwang, Samsung Electronics. The conference papers and full proceedings are available to registered attendees now and will be available to everyone beginning Wednesday, July 14, 2021. Contact your program co-chairs, osdi21chairs@usenix.org, or the USENIX office, submissionspolicy@usenix.org. We observe that scalability challenges in training GNNs are fundamentally different from that in training classical deep neural networks and distributed graph processing; and that commonly used techniques, such as intelligent partitioning of the graph do not yield desired results. NrOS is primarily constructed as a simple, sequential kernel with no concurrency, making it easier to develop and reason about its correctness. Our evaluation on the SPEC benchmarks shows that SanRazor can reduce the overhead of sanitizers significantly, from 73.8% to 28.062.0% for AddressSanitizer, and from 160.1% to 36.6124.4% for UndefinedBehaviorSanitizer (depending on the applied reduction scheme). In addition, CLP outperforms Elasticsearch and Splunk Enterprise's log ingestion performance by over 13x, and we show CLP scales to petabytes of logs. As a result, the design of a file system with respect to space management and crash consistency is simplified, requiring only 10.8K LOC for full functionality. Dorylus is up to 3.8 faster and 10.7 cheaper compared to existing sampling-based systems. Prepublication versions of the accepted papers from the summer submission deadline are available below. OSDI is "a premier forum for discussing the design, implementation, and implications of systems software." A total of six research papers from the department were accepted to the . Mothy joined the Computer Science Department ETH Zurich in January 2007 and was named Fellow of the ACM in 2013 for contributions to operating systems and networking research. Federated Learning (FL) is an emerging direction in distributed machine learning (ML) that enables in-situ model training and testing on edge data. Our evaluation shows that DistAI successfully verifies 13 common distributed protocols automatically and outperforms alternative methods both in the number of protocols it verifies and the speed at which it does so, in some cases by more than two orders of magnitude. Editor in charge: Daniel Petrolia . Sep 2021 - Present 1 year 7 months. . Existing frameworks optimize tensor programs by applying fully equivalent transformations, which maintain equivalence on every element of output tensors. PET discovers and applies program transformations that improve computation efficiency but only maintain partial functional equivalence. We built a functional NFSv3 server, called GoNFS, to use GoJournal. For any further information, please contact the PC chairs: pc-chairs-2022@eurosys.org. We observe that, due to their intended security guarantees, SC schemes are inherently oblivioustheir memory access patterns are independent of the input data. Papers not meeting these criteria will be rejected without review, and no deadline extensions will be granted for reformatting. We propose a learning-based framework that instead explicitly optimizes concurrency control via offline training to maximize performance. Attaching supplementary material is optional; if your paper says that you have source code or formal proofs, you need not attach them to convince the PC of their existence. If your accepted paper should not be published prior to the event, please notify production@usenix.org. OSDI'21 accepted 31 papers and 26 papers participated in the AE, a significant increase in the participate ratio: 84%, compared to OSDI'20 (70%) and SOSP'19 (61%). We also show that Marius can scale training to datasets an order of magnitude beyond a single machine's GPU and CPU memory capacity, enabling training of configurations with more than a billion edges and 550 GB of total parameters on a single machine with 16 GB of GPU memory and 64 GB of CPU memory. Computation separation makes it possible to construct a deep, bounded-asynchronous pipeline where graph and tensor parallel tasks can fully overlap, effectively hiding the network latency incurred by Lambdas. Although SSDs can be simplified under the current ZNS interface, its counterpart LFS must bear segment compaction overhead. We describe Fluffy, a multi-transaction differential fuzzer for finding consensus bugs in Ethereum. A graph neural network (GNN) enables deep learning on structured graph data. Consensus bugs are extremely rare but can be exploited for network split and theft, which cause reliability and security-critical issues in the Ethereum ecosystem. Graph Neural Networks (GNNs) have gained significant attention in the recent past, and become one of the fastest growing subareas in deep learning. We propose Marius, a system for efficient training of graph embeddings that leverages partition caching and buffer-aware data orderings to minimize disk access and interleaves data movement with computation to maximize utilization. To resolve the problem, we propose a new LFS-aware ZNS interface, called ZNS+, and its implementation, where the host can offload data copy operations to the SSD to accelerate segment compaction. Pollux improves scheduling performance in deep learning (DL) clusters by adaptively co-optimizing inter-dependent factors both at the per-job level and at the cluster-wide level. Our evaluation shows that NrOS scales to 96 cores with performance that nearly always dominates Linux at scale, in some cases by orders of magnitude, while retaining much of the simplicity of a sequential kernel. For general conference information, see https://www . HotNets provides a venue for discussing innovative ideas and for debating future research agendas in networking. Unfortunately, because devices lack the semantic information about which I/O requests are latency-sensitive, these heuristics can sometimes lead to disastrous results. 23 artifacts received the Artifacts Functional badge (88%). Jiachen Wang, Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University; Shanghai AI Laboratory; Engineering Research Center for Domain-specific Operating Systems, Ministry of Education, China; Ding Ding, Department of Computer Science, New York University; Huan Wang, Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University; Shanghai AI Laboratory; Engineering Research Center for Domain-specific Operating Systems, Ministry of Education, China; Conrad Christensen, Department of Computer Science, New York University; Zhaoguo Wang and Haibo Chen, Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University; Shanghai AI Laboratory; Engineering Research Center for Domain-specific Operating Systems, Ministry of Education, China; Jinyang Li, Department of Computer Science, New York University. These are hard deadlines, and no extensions will be given. In particular, I'll argue for re-engaging with what computer hardware really is today and give two suggestions (among many) about how the OS research community can usefully do this, and exploit what is actually a tremendous opportunity. We implemented the ZNS+ SSD at an SSD emulator and a real SSD. This paper demonstrates that it is possible to achieve s-scale latency using Linux kernel storage stack, even when tens of latency-sensitive applications compete for host resources with throughput-bound applications that perform read/write operations at throughput close to hardware capacity. Moreover, to handle dynamic workloads, Nap adopts a fast NAL switch mechanism. We particularly encourage contributions containing highly original ideas, new approaches, and/or groundbreaking results. See the Preview Session page for an overview of the topics covered in the program. Welcome to the 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI '22) submissions site. While compiler-based techniques have been proposed to improve data locality, they depend on heuristics, which can sometimes hurt performance. For realistic workloads, KEVIN improves throughput by 68% on average. Four months after we reported the bugs to Geth developers, one of the bugs was triggered on the mainnet, and caused nodes using a stale version of Geth to hard fork the Ethereum blockchain. Calibrated interrupts increase throughput by up to 35%, reduce CPU consumption by as much as 30%, and achieve up to 37% lower latency when interrupts are coalesced. Academic and industrial participants present research and experience papers that cover the full range of theory and practice of computer . In this paper, we propose Oort to improve the performance of federated training and testing with guided participant selection. Uniquely, Dorylus can take advantage of serverless computing to increase scalability at a low cost.
What Happened To Versacheck,
Who Is Tracy Relief Factor Commercial,
The Rhpc Squad Will Paco Pacarro,
Fort Pierce News Shooting,
A Streetcar Named Desire Genre,
Articles O