Ethereum is the second-largest blockchain platform next to Bitcoin. Message from the Program Co-Chairs. 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% Writing a correct operating system kernel is notoriously hard. If the conference registration fee will pose a hardship for the presenter of the accepted paper, please contact conference@usenix.org. However, the existing one-size-fits-all GNN implementations are insufficient to catch up with the evolving GNN architectures, the ever-increasing graph size, and the diverse node embedding dimensionality. Novel system designs, thorough empirical work, well-motivated theoretical results, and new application areas are all . OSDI 2021 papers summary. By submitting a paper, you agree that at least one of the authors will attend the conference to present it. Currently, for large graphs, CPU servers offer the best performance-per-dollar over GPU servers. Because DistAI starts with the strongest possible invariants, if the SMT solver fails, DistAI does not need to discard failed invariants, but knows to monotonically weaken them and try again with the solver, repeating the process until it eventually succeeds. Cores can safely and concurrently read from their local kernel replica, eliminating remote NUMA accesses. Research Impact Score 9.24. . We propose PET, the first DNN framework that optimizes tensor programs with partially equivalent transformations and automated corrections. Using selective profiling, we build DMon, a system that can automatically locate data locality problems in production, identify access patterns that hurt locality, and repair such patterns using targeted optimizations. Just using Lambdas on top of CPU servers offers up to 2.75 more performance-per-dollar than training only with CPU servers. Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, and Yufei Ding, University of California, Santa Barbara. When registering your abstract, you must provide information about conflicts with PC members. 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. AI enables principled representation of knowledge, complex strategy optimization, learning from data, and support to human decision making. Notification of conditional accept/reject for revisions: 3 March 2022. Web pages today commonly include large amounts of JavaScript code in order to offer users a dynamic experience. She has a PhD in computer science from MIT. Compared to a state-of-the-art fuzzer, Fluffy improves the fuzzing throughput by 510 and the code coverage by 2.7 with various optimizations: in-process fuzzing, fuzzing harnesses for Ethereum clients, and semantic-aware mutation that reduces erroneous test cases. The novel aspect of the nanoPU is the design of a fast path between the network and applications---bypassing the cache and memory hierarchy, and placing arriving messages directly into the CPU register file. Main conference program: 5-8 April 2022. This fast path contains programmable hardware support for low latency transport and congestion control as well as hardware support for efficient load balancing of RPCs to cores. PLDI seeks outstanding research that extends and/or applies programming-language concepts to advance the field of computing. Professor Veloso is the Past President of AAAI (the Association for the Advancement of Artificial Intelligence), and the co-founder, Trustee, and Past President of RoboCup. 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 present DPF (Dominant Private Block Fairness) a variant of the popular Dominant Resource Fairness (DRF) algorithmthat is geared toward the non-replenishable privacy resource but enjoys similar theoretical properties as DRF. USENIX discourages program co-chairs from submitting papers to the conferences they organize, although they are allowed to do so. After request completion, an I/O device must decide either to minimize latency by immediately firing an interrupt or to optimize for throughput by delaying the interrupt, anticipating that more requests will complete soon and help amortize the interrupt cost. SanRazor adopts a novel hybrid approach it captures both dynamic code coverage and static data dependencies of checks, and uses the extracted information to perform a redundant check analysis. Instead, we propose addressing the root cause of the heuristics problem by allowing software to explicitly specify to the device if submitted requests are latency-sensitive. OSDI brings together professionals from academic and industrial backgrounds in a premier forum for discussing the design, implementation, and implications of systems software. 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, existing enclave designs fail to meet the requirements of scalability demanded by new scenarios like serverless computing, mainly due to the limitations in their secure memory protection mechanisms, including static allocation, restricted capacity and high-cost initialization. Submitted papers must be no longer than 12 single-spaced 8.5 x 11 pages, including figures and tables, plus as many pages as needed for references, using 10-point type on 12-point (single-spaced) leading, two-column format, Times Roman or a similar font, within a text block 7 wide x 9 deep. Session Chairs: Sebastian Angel, University of Pennsylvania, and Malte Schwarzkopf, Brown University, Ishtiyaque Ahmad, Yuntian Yang, Divyakant Agrawal, Amr El Abbadi, and Trinabh Gupta, University of California Santa Barbara. As increasingly more sensitive data is being collected to gain valuable insights, the need to natively integrate privacy controls in data analytics frameworks is growing in importance. The NAL eliminates remote PM accesses to hot items without inducing extra local PM accesses. Unfortunately, because devices lack the semantic information about which I/O requests are latency-sensitive, these heuristics can sometimes lead to disastrous results. For general conference information, see https://www . 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. 23 artifacts received the Artifacts Functional badge (88%). Existing decentralized systems like Steemit, OpenBazaar, and the growing number of blockchain apps provide alternatives to existing services. See the Preview Session page for an overview of the topics covered in the program. We prove that DistAI is guaranteed to find the -free inductive invariant that proves the desired safety properties in finite time, if one exists. 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. How can we design systems that will be reliable despite misbehaving participants? Important Dates Abstract registrations due: Thursday, December 3, 2020, 3:00 pm PST Complete paper submissions due: Thursday, December 10, 2020, 3:00pm PST Author Response Period Swapnil Gandhi and Anand Padmanabha Iyer, Microsoft Research. First, GNNAdvisor explores and identifies several performance-relevant features from both the GNN model and the input graph, and use them as a new driving force for GNN acceleration. Welcome to the 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI '21) submissions site. While several new GNN architectures have been proposed, the scale of real-world graphsin many cases billions of nodes and edgesposes challenges during model training. Only two types of supplementary material are permitted: source code described in the paper and formal proofs sketched in the paper. In this talk, I'll speculate on how we came to this unfortunate state of affairs, and what might be done to fix it. Erhu Feng, Xu Lu, Dong Du, Bicheng Yang, and Xueqiang Jiang, Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University; Engineering Research Center for Domain-specific Operating Systems, Ministry of Education, China; Yubin Xia, Binyu Zang, 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. Jiang Zhang, University of Southern California; Shuai Wang, HKUST; Manuel Rigger, Pinjia He, and Zhendong Su, ETH Zurich. In some cases, the quality of these artifacts is as important as that of the document itself. She developed the technology for making network routing self-stabilizing, largely self-managing, and scalable. If your accepted paper should not be published prior to the event, please notify production@usenix.org. However, Addra improves message latency in this architecture, which is a key performance metric for voice calls. With her students, she had led research in AI, with a focus on robotics and machine learning, having concretely researched and developed a variety of autonomous robots, including teams of soccer robots, and mobile service robots. J.P. Morgan AI Research partners with applied data analytics teams across the firm as well as with leading academic institutions globally. See www.cs.cmu.edu/~mmv/Veloso.html for her scientific publications. Prior or concurrent publication in non-peer-reviewed contexts, like arXiv.org, technical reports, talks, and social media posts, is permitted. DistAI: Data-Driven Automated Invariant Learning for Distributed Protocols Jianan Yao, Runzhou Tao, Ronghui Gu, Jason Nieh . 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) Devices employ adaptive interrupt coalescing heuristics that try to balance between these opposing goals. Authors should email the program co-chairs, osdi21chairs@usenix.org, a copy of the related workshop paper and a short explanation of the new material in the conference paper beyond that published in the workshop version. Marius is open-sourced at www.marius-project.org. Based on this observation, P3 proposes a new approach for distributed GNN training. We present case studies and end-to-end applications that show how Storm lets developers specify diverse policies while centralizing the trusted code to under 1% of the application, and statically enforces security with modest type annotation overhead, and no run-time cost. Hence, kernel developers are constantly refining synchronization within OS kernels to improve scalability at the risk of introducing subtle bugs. Leveraging these information, Pollux dynamically (re-)assigns resources to improve cluster-wide goodput, while respecting fairness and continually optimizing each DL job to better utilize those resources. USENIX new Date().getFullYear()>document.write(new Date().getFullYear()); Grants for Black Computer Science Students Application, Propose an interesting, compelling solution, Demonstrate the practicality and benefits of the solution, Clearly describe the paper's contributions, Clearly articulate the advances beyond previous work. Jaehyun Hwang and Midhul Vuppalapati, Cornell University; Simon Peter, UT Austin; Rachit Agarwal, Cornell University. Academic and industrial participants present research and experience papers that cover the full range of theory . One important reason for the high cost is, as we observe in this paper, that many sanitizer checks are redundant the same safety property is repeatedly checked leading to unnecessarily wasted computing resources. The chairs will review paper conflicts to ensure the integrity of the reviewing process, adding or removing conflicts if necessary. Horcruxs JavaScript scheduler then uses this information to judiciously parallelize JavaScript execution on the client-side so that the end-state is identical to that of a serial execution, while minimizing coordination and offloading overheads. GoJournal is implemented in Go, and Perennial is implemented in the Coq proof assistant. We build Polyjuice based on our learning framework and evaluate it against several existing algorithms. Despite having the same end goals as traditional ML, FL executions differ significantly in scale, spanning thousands to millions of participating devices. For conference information, . We have implemented a prototype of our design based on Penglai, an open-sourced enclave system for RISC-V. DMons targeted optimizations provide 16.83% speedup on average (up to 53.14%), compared to a baseline that uses the highest level of compiler optimization. For more details on the submission process, and for templates to use with LaTeX, Word, etc., authors should consult the detailed submission requirements. Additionally, there is no assurance that data processing and handling comply with the claimed privacy policies. Compared to existing baselines, DPF allows training more models under the same global privacy guarantee. We present selective profiling, a technique that locates data locality problems with low-enough overhead that is suitable for production use. Manuela M. Veloso is the Head of J.P. Morgan AI Research, which pursues fundamental research in areas of core relevance to financial services, including data mining and cryptography, machine learning, explainability, and human-AI interaction. Kyuhwa Han, Sungkyunkwan University and Samsung Electronics; Hyunho Gwak and Dongkun Shin, Sungkyunkwan University; Jooyoung Hwang, Samsung Electronics. Registering abstracts a week before paper submission is an essential part of the paper-reviewing process, as PC members use this time to identify which papers they are qualified to review. 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. There is no explicit limit to the response, but authors are strongly encouraged to keep it under 500 words; reviewers are neither required nor expected to read excessively long responses. Abstract registrations that do not provide sufficient information to understand the topic and contribution (e.g., empty abstracts, placeholder abstracts, or trivial abstracts) will be rejected, thereby precluding paper submission. Camera-ready submission (all accepted papers): 15 Mars 2022. Upon these two primitives, our system can scale to thousands of concurrent enclaves with high resource utilization and eliminate the high-cost initialization of secure memory using fork-style enclave creation without weakening the security guarantees. The ZNS+ also allows each zone to be overwritten with sparse sequential write requests, which enables the LFS to use threaded logging-based block reclamation instead of segment compaction. Machine learning (ML) models trained on personal data have been shown to leak information about users. The biennial ACM Symposium on Operating Systems Principles is the world's premier forum for researchers, developers, programmers, vendors and teachers of operating system technology. PET discovers and applies program transformations that improve computation efficiency but only maintain partial functional equivalence. By monitoring the status of each job during training, Pollux models how their goodput (a novel metric we introduce that combines system throughput with statistical efficiency) would change by adding or removing resources. 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. These limitations require state-of-the-art systems to distribute training across multiple machines. We present DistAI, a data-driven automated system for learning inductive invariants for distributed protocols. We implement and evaluate a suite of applications, including MICA, Raft and Set Algebra for document retrieval; and we demonstrate that the nanoPU can be used as a high performance, programmable alternative for one-sided RDMA operations. This paper presents Zeph, a system that enables users to set privacy preferences on how their data can be shared and processed. This paper addresses a key missing piece in the current ecosystem of decentralized services and blockchain apps: the lack of decentralized, verifiable, and private search. . Mingyu Li, Jinhao Zhu, and Tianxu Zhang, 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; Cheng Tan, Northeastern University; Yubin Xia, 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; Sebastian Angel, University of Pennsylvania; 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. This approach misses possible optimization opportunities as transformations that only preserve equivalence on subsets of the output tensors are excluded. We first introduce two new hardware primitives: 1) Guarded Page Table (GPT), which protects page table pages to support page-level secure memory isolation; 2) Mountable Merkle Tree (MMT), which supports scalable integrity protection for secure memory. The key insight guiding our design is computation separation. Extensive experiments show that GNNAdvisor outperforms the state-of-the-art GNN computing frameworks, such as Deep Graph Library (3.02 faster on average) and NeuGraph (up to 4.10 faster), on mainstream GNN architectures across various datasets. Graph Neural Networks (GNNs) have gained significant attention in the recent past, and become one of the fastest growing subareas in deep learning. Professor Veloso is on leave from Carnegie Mellon University as the Herbert A. Simon University Professor in the School of Computer Science, and the past Head of the Machine Learning Department. Metadata from voice calls, such as the knowledge of who is communicating with whom, contains rich information about peoples lives. OSDI '21 Technical Sessions All the times listed below are in Pacific Daylight Time (PDT). With an aim to improve time-to-accuracy performance in model training, Oort prioritizes the use of those clients who have both data that offers the greatest utility in improving model accuracy and the capability to run training quickly. Authors must limit their responses to (a) correcting factual errors in the reviews or (b) directly addressing questions posed by reviewers. Prior or concurrent workshop publication does not preclude publishing a related paper in OSDI. Taking place in Carlsbad, CA from 11-13 July, OSDI is a highly selective flagship conference in computer science, especially on the topic of computer systems. We also propose two file system techniques for ZNS+-aware LFS. The overhead of GPT is 5% for memory-intensive workloads (e.g., Redis) and negligible for CPU-intensive workloads (e.g., RV8 and Coremarks). Session Chairs: Deniz Altinbken, Google, and Rashmi Vinayak, Carnegie Mellon University, Tanvir Ahmed Khan and Ian Neal, University of Michigan; Gilles Pokam, Intel Corporation; Barzan Mozafari and Baris Kasikci, University of Michigan.