He joined Intel Research at Berkeley in April 2002 as a principal architect of PlanetLab, an open, shared platform for developing and deploying planetary-scale services. 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. Horcrux-compliant web servers perform offline analysis of all the JavaScript code on any frame they serve to conservatively identify, for every JavaScript function, the union of the page state that the function could access across all loads of that page. The papers will be available online to everyone beginning on the first day of the conference, July 14, 2021. Qing Wang, Youyou Lu, Junru Li, and Jiwu Shu, Tsinghua University. The program co-chairs will use this information at their discretion to preserve the anonymity of the review process without jeopardizing the outcome of the current OSDI submission. Owing to the sequential write-only zone scheme of the ZNS, the log-structured file system (LFS) is required to access ZNS solid-state drives (SSDs). Last year, 70% of accepted OSDI papers participated in the . Session Chairs: Ryan Huang, Johns Hopkins University, and Manos Kapritsos, University of Michigan, Jianan Yao, Runzhou Tao, Ronghui Gu, Jason Nieh, Suman Jana, and Gabriel Ryan, Columbia University. Widely used log-search tools like Elasticsearch and Splunk Enterprise index the logs to provide fast search performance, yet the size of the index is within the same order of magnitude as the raw log size. Lifting predicates and crash framing make the specification easy to use for developers, and logically atomic crash specifications allow for modular reasoning in GoJournal, making the proof tractable despite complex concurrency and crash interleavings. 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. Some recent schedulers choose job resources for users, but do so without awareness of how DL training can be re-optimized to better utilize the provided resources. The hybrid segment recycling chooses a proper block reclaiming policy between segment compaction and threaded logging based on their costs. One classical approach is to increase the efficiency of an allocator to minimize the cycles spent in the allocator code. 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. Pollux is implemented and publicly available as part of an open-source project at https://github.com/petuum/adaptdl. 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. Moreover, as of October 2020, a review of the 50 most cited empirical papers that list personality as a keyword indicates that all 50 papers were authored by people with insti tutional affiliations in the United States, Canada, Germany, the UK, and New Zealand, and only three papers included samples outside of these regions (see Supplementary 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 We develop rigorous theoretical foundations to simplify equivalence examination and correction for partially equivalent transformations, and design an efficient search algorithm to quickly discover highly optimized programs by combining fully and partially equivalent optimizations at the tensor, operator, and graph levels. We evaluate PrivateKube and DPF on microbenchmarks and an ML workload on Amazon Reviews data. Furthermore, by combining SanRazor with an existing sanitizer reduction tool ASAP, we show synergistic effect by reducing the runtime cost to only 7.0% with a reasonable tradeoff of security. 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. 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. His work has included the Barrelfish multikernel research OS, as well as work on distributed stream processors, and using formal specifications to describe the hardware/software interfaces of modern computer systems. They collectively make the backup fresh, columnar, and fault-tolerant, even facing millions of concurrent transactions per second. For conference information, . HotNets provides a venue for discussing innovative ideas and for debating future research agendas in networking. Only two types of supplementary material are permitted: source code described in the paper and formal proofs sketched in the paper. This is unfortunate because good OS design has always been driven by the underlying hardware, and right now that hardware is almost unrecognizable from ten years ago, let alone from the 1960s when Unix was written. However, memory allocation decisions also impact overall application performance via data placement, offering opportunities to improve fleetwide productivity by completing more units of application work using fewer hardware resources. Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, and Yufei Ding, University of California, Santa Barbara. Machine learning (ML) models trained on personal data have been shown to leak information about users. Second, Fluffy uses multiple existing Ethereum clients that independently implement the specification as cross-referencing oracles. My paper has accepted to appear in the EuroSys2020; I will have a talk at the Hotstorage'19; The Paper about GCMA Accepted to TC; 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. (Visa applications can take at least 30 working days to process.) We implement DeSearch for two existing decentralized services that handle over 80 million records and 240 GBs of data, and show that DeSearch can scale horizontally with the number of workers and can process 128 million search queries per day. GoJournal is implemented in Go, and Perennial is implemented in the Coq proof assistant. We will look at various problems and approaches, and for each, see if blockchain would help. These are hard deadlines, and no extensions will be given. 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. The 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI '21) will take place as a virtual event on July 14-16, 2021. We focus on NVMe storage devices and show that it is natural to express these semantics in the kernel and the application and only requires a modest two-bit change to the device interface. Furthermore, such performance can be achieved without any modification in applications, network hardware, kernel CPU schedulers and/or kernel network stack. Fan Lai, Xiangfeng Zhu, Harsha V. Madhyastha, and Mosharaf Chowdhury, University of Michigan. Hence, CLP enables efficient search and analytics on archived logs, something that was impossible without it. We prove that DistAI is guaranteed to find the -free inductive invariant that proves the desired safety properties in finite time, if one exists. 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. For general conference information, see https://www . However, your OSDI submission must use an anonymized name for your project or system that differs from any used in such contexts. Pollux promotes fairness among DL jobs competing for resources based on a more meaningful measure of useful job progress, and reveals a new opportunity for reducing DL cost in cloud environments. The OSDI Symposium emphasizes innovative research as well as quantified or insightful experiences in systems design and implementation. We describe PrivateKube, an extension to the popular Kubernetes datacenter orchestrator that adds privacy as a new type of resource to be managed alongside other traditional compute resources, such as CPU, GPU, and memory. If in doubt about whether your submission to OSDI 2021 and your upcoming submission to SOSP are the same paper or not, please contact the PC chairs by email. If you are uncertain about how to anonymize your submission, please contact the program co-chairs, osdi21chairs@usenix.org, well in advance of the submission deadline. In this paper, we propose a software-hardware co-design to support dynamic, fine-grained, large-scale secure memory as well as fast-initialization. Authors may submit a response to those reviews until Friday, March 5, 2021. . In particular, responses must not include new experiments or data, describe additional work completed since submission, or promise additional work to follow. USENIX, like other scientific and technical conferences and journals, prohibits these practices and may, on the recommendation of a program chair, take action against authors who have committed them. AI enables principled representation of knowledge, complex strategy optimization, learning from data, and support to human decision making. Our approach outperforms existing file systems on a block SSD by a wide margin 6.2 on average for metadata-intensive benchmarks. Jiang Zhang, University of Southern California; Shuai Wang, HKUST; Manuel Rigger, Pinjia He, and Zhendong Su, ETH Zurich. 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. Editor in charge: Daniel Petrolia . When registering your abstract, you must provide information about conflicts with PC members. See the USENIX Conference Submissions Policy for details. Academic and industrial participants present research and experience papers that cover the full range of theory and practice of computer . Proceedings Front Matter A graph embedding is a fixed length vector representation for each node (and/or edge-type) in a graph and has emerged as the de-facto approach to apply modern machine learning on graphs. Sanitizers detect unsafe actions such as invalid memory accesses by inserting checks that are validated during a programs execution. An evaluation of Addra on a cluster of 80 machines on AWS demonstrates that it can serve 32K users with a 99-th percentile message latency of 726 msa 7 improvement over a prior system for text messaging in the same threat model. For example, optimistic concurrency control (OCC) is better than two-phase-locking (2PL) under low contention, while the converse is true under high contention. Just using Lambdas on top of CPU servers offers up to 2.75 more performance-per-dollar than training only with CPU servers. 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. 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. Therefore, developers typically find data locality issues via dynamic profiling and repair them manually. Sam Kumar, David E. Culler, and Raluca Ada Popa, University of California, Berkeley. 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. Differential privacy (DP) enables model training with a guaranteed bound on this leakage. Shaghayegh Mardani, UCLA; Ayush Goel, University of Michigan; Ronny Ko, Harvard University; Harsha V. Madhyastha, University of Michigan; Ravi Netravali, Princeton University. 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. However, a plethora of recent data breaches show that even widely trusted service providers can be compromised. Federated Learning (FL) is an emerging direction in distributed machine learning (ML) that enables in-situ model training and testing on edge data. 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. 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. 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. Papers must be in PDF format and must be submitted via the submission form. We implemented the ZNS+ SSD at an SSD emulator and a real SSD. This distinction forces a re-design of the scheduler. How can we design systems that will be reliable despite misbehaving participants? We built a functional NFSv3 server, called GoNFS, to use GoJournal. Password We present DistAI, a data-driven automated system for learning inductive invariants for distributed protocols. This paper presents Zeph, a system that enables users to set privacy preferences on how their data can be shared and processed. Writing a correct operating system kernel is notoriously hard. Despite having the same end goals as traditional ML, FL executions differ significantly in scale, spanning thousands to millions of participating devices. In the Ethereum network, decentralized Ethereum clients reach consensus through transitioning to the same blockchain states according to the Ethereum specification. A hardware-accelerated thread scheduler makes sub-nanosecond decisions, leading to high CPU utilization and low tail response time for RPCs. She has a PhD in computer science from MIT. Timothy Roscoe is a Full Professor in the Systems Group of the Computer Science Department at ETH Zurich, where he works on operating systems, networks, and distributed systems, and is currently head of department. Perennial 2.0 makes this possible by introducing several techniques to formalize GoJournals specification and to manage the complexity in the proof of GoJournals implementation. ), Program Co-Chairs: Angela Demke Brown, University of Toronto, and Jay Lorch, Microsoft Research. You must not improperly identify a PC member as a conflict if none of these three circumstances applies, even if for some other reason you want to avoid them reviewing your paper. Penglai also reduces the latency of secure memory initialization by three orders of magnitude and gains 3.6x speedup for real-world applications (e.g., MapReduce). Alas, existing profiling techniques incur high overhead when used to identify data locality problems and cannot be deployed in production, where programs may exhibit previously-unseen performance problems. She is the recipient of several best paper awards, the Einstein Chair of the Chinese Academy of Science, the ACM/SIGART Autonomous Agents Research Award, an NSF Career Award, and the Allen Newell Medal for Excellence in Research. Third, GNNAdvisor capitalizes on the GPU memory hierarchy for acceleration by gracefully coordinating the execution of GNNs according to the characteristics of the GPU memory structure and GNN workloads. 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. A scientific paper consists of a constellation of artifacts that extend beyond the document itself: software, hardware, evaluation data and documentation, raw survey results, mechanized proofs, models, test suites, benchmarks, and so on. Paper abstracts and proceedings front matter are available to everyone now. The file system performance of the proposed ZNS+ storage system was 1.33--2.91 times better than that of the normal ZNS-based storage system. Questions? With the help of thousands of Lambda threads, Dorylus scales GNN training to billion-edge graphs. 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. If your accepted paper should not be published prior to the event, please notify production@usenix.org. The main contribution of this paper is GoJournal, a verified, concurrent journaling system that provides atomicity for storage applications, together with Perennial 2.0, a framework for formally specifying and verifying concurrent crash-safe systems. We compare Marius against two state-of-the-art industrial systems on a diverse array of benchmarks. We present Storm, a web framework that allows developers to build MVC applications with compile-time enforcement of centrally specified data-dependent security policies. For instance, FAST 21 and NSDI 21 have author-notification dates after the OSDI 21 abstract-registration deadline. OSDI brings together professionals from academic and industrial backgrounds in a premier forum for discussing the design, implementation, and implications of systems software. Reviews will be available for response on Wednesday, March 3, 2021. This kernel is scaled across NUMA nodes using node replication, a scheme inspired by state machine replication in distributed systems. The wire-to-wire RPC response time through the nanoPU is just 69ns, an order of magnitude quicker than the best-of-breed, low latency, commercial NICs. Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning, Oort: Efficient Federated Learning via Guided Participant Selection, PET: Optimizing Tensor Programs with Partially Equivalent Transformations and Automated Corrections, Modernizing File System through In-Storage Indexing, Nap: A Black-Box Approach to NUMA-Aware Persistent Memory Indexes, Rearchitecting Linux Storage Stack for s Latency and High Throughput, Optimizing Storage Performance with Calibrated Interrupts, ZNS+: Advanced Zoned Namespace Interface for Supporting In-Storage Zone Compaction, DMon: Efficient Detection and Correction of Data Locality Problems Using Selective Profiling, CLP: Efficient and Scalable Search on Compressed Text Logs, Polyjuice: High-Performance Transactions via Learned Concurrency Control, Retrofitting High Availability Mechanism to Tame Hybrid Transaction/Analytical Processing, The nanoPU: A Nanosecond Network Stack for Datacenters, Beyond malloc efficiency to fleet efficiency: a hugepage-aware memory allocator, Scalable Memory Protection in the PENGLAI Enclave, NrOS: Effective Replication and Sharing in an Operating System, Addra: Metadata-private voice communication over fully untrusted infrastructure, Bringing Decentralized Search to Decentralized Services, Finding Consensus Bugs in Ethereum via Multi-transaction Differential Fuzzing, MAGE: Nearly Zero-Cost Virtual Memory for Secure Computation, Zeph: Cryptographic Enforcement of End-to-End Data Privacy, It's Time for Operating Systems to Rediscover Hardware, DistAI: Data-Driven Automated Invariant Learning for Distributed Protocols, GoJournal: a verified, concurrent, crash-safe journaling system, STORM: Refinement Types for Secure Web Applications, Horcrux: Automatic JavaScript Parallelism for Resource-Efficient Web Computation, SANRAZOR: Reducing Redundant Sanitizer Checks in C/C++ Programs, Dorylus: Affordable, Scalable, and Accurate GNN Training with Distributed CPU Servers and Serverless Threads, GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs, Marius: Learning Massive Graph Embeddings on a Single Machine, P3: Distributed Deep Graph Learning at Scale. Kirk Rodrigues, Yu Luo, and Ding Yuan, University of Toronto and YScope Inc. DistAI: Data-Driven Automated Invariant Learning for Distributed Protocols Jianan Yao, Runzhou Tao, Ronghui Gu, Jason Nieh . Copyright to the individual works is retained by the author[s]. 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. We identify that current systems for learning the embeddings of large-scale graphs are bottlenecked by data movement, which results in poor resource utilization and inefficient training. DeSearch then introduces a witness mechanism to make sure the completed tasks can be reused across different pipelines, and to make the final search results verifiable by end users. Uniquely, Dorylus can take advantage of serverless computing to increase scalability at a low cost. To adapt to different workloads, prior works mix or switch between a few known algorithms using manual insights or simple heuristics. The abstractions we design for the privacy resource mirror those defined by Kubernetes for traditional resources, but there are also major differences. Table of Contents | 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. Her specialties include network routing protocols and network security. Poor data locality hurts an application's performance. 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) Finding the inductive invariant of the distributed protocol is a critical step in verifying the correctness of distributed systems, but takes a long time to do even for simple protocols. 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. OSDI brings together professionals from academic and industrial backgrounds in what has become a premier forum for discussing the design, implementation, and implications of systems software. Manuela will present examples and discuss the scope of AI in her research in the finance domain. sosp ACM Symposium on Operating Systems Principles. Memory allocation represents significant compute cost at the warehouse scale and its optimization can yield considerable cost savings. Ankit Bhardwaj and Chinmay Kulkarni, University of Utah; Reto Achermann, University of British Columbia; Irina Calciu, VMware Research; Sanidhya Kashyap, EPFL; Ryan Stutsman, University of Utah; Amy Tai and Gerd Zellweger, VMware Research. 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. J.P. Morgan AI Research partners with applied data analytics teams across the firm as well as with leading academic institutions globally. Weak Links in Authentication Chains: A Large-scale Analysis of Email Sender Spoofing Attacks 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. 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. 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. Simultaneous submission of the same work to multiple venues, submission of previously published work, or plagiarism constitutes dishonesty or fraud. The 15th USENIX Symposium on Operating Systems Design and Implementation seeks to present innovative, exciting research in computer systems. If you submit a paper to either of those venues, you may not also submit it to OSDI 21. Tao Luo, Mingen Pan, Pierre Tholoniat, Asaf Cidon, and Roxana Geambasu, Columbia University; Mathias Lcuyer, Microsoft Research. 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. USENIX discourages program co-chairs from submitting papers to the conferences they organize, although they are allowed to do so. We conclude with a discussion of additional techniques for improving the allocator development process and potential optimization strategies for future memory allocators. For conference information, see: . Foreshadow was chosen as an IEEE Micro Top Pick. Fortunately, we observe that the backups for high availability in modern distributed OLTP systems can be retrofitted to bridge the analytical queries and transactions in HTAP workloads. Radia Perlman is a Fellow at Dell Technologies. Authors may upload supplementary material in files separate from their submissions. 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. We propose a new framework for computing the embeddings of large-scale graphs on a single machine. Jason Mohoney and Roger Waleffe, University of WisconsinMadison; Henry Xu, University of Maryland, College Park; Theodoros Rekatsinas and Shivaram Venkataraman, University of WisconsinMadison. 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. We have implemented a prototype of our design based on Penglai, an open-sourced enclave system for RISC-V. In addition, increasing CPU core counts further complicate kernel development. Tej Chajed, MIT CSAIL; Joseph Tassarotti, Boston College; Mark Theng, MIT CSAIL; Ralf Jung, MPI-SWS; M. Frans Kaashoek and Nickolai Zeldovich, MIT CSAIL. For more details on the submission process, and for templates to use with LaTeX, Word, etc., authors should consult the detailed submission requirements. The overhead of GPT is 5% for memory-intensive workloads (e.g., Redis) and negligible for CPU-intensive workloads (e.g., RV8 and Coremarks). In some cases, the quality of these artifacts is as important as that of the document itself. Prior or concurrent workshop publication does not preclude publishing a related paper in OSDI.
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