Grand Rapids, Michigan, United States . USENIX Security '21 has three submission deadlines. Submissions violating the detailed formatting and anonymization rules will not be considered for review. 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. She developed the technology for making network routing self-stabilizing, largely self-managing, and scalable. Prior or concurrent workshop publication does not preclude publishing a related paper in OSDI. She also has made contributions in network security, including scalable data expiration, distributed algorithms despite malicious participants, and DDOS prevention techniques. Session Chairs: Nadav Amit, VMware Research Group, and Ada Gavrilovska, Georgia Institute of Technology, Stephen Ibanez, Alex Mallery, Serhat Arslan, and Theo Jepsen, Stanford University; Muhammad Shahbaz, Purdue University; Changhoon Kim and Nick McKeown, Stanford University. In 2023 I started another two-year term on the . Differential privacy (DP) enables model training with a guaranteed bound on this leakage. Jiang Zhang, University of Southern California; Shuai Wang, HKUST; Manuel Rigger, Pinjia He, and Zhendong Su, ETH Zurich. We built an FPGA prototype of the nanoPU fast path by modifying an open-source RISC-V CPU, and evaluated its performance using cycle-accurate simulations on AWS FPGAs. Editor in charge: Daniel Petrolia . Title Page, Copyright Page, and List of Organizers | Web pages today commonly include large amounts of JavaScript code in order to offer users a dynamic experience. 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. 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. We present Storm, a web framework that allows developers to build MVC applications with compile-time enforcement of centrally specified data-dependent security policies. We present application studies for 8 applications, improving requests-per-second (RPS) by 7.7% and reducing RAM usage 2.4%. This paper presents Zeph, a system that enables users to set privacy preferences on how their data can be shared and processed. 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. Conference site 49 papers accepted out of 251 submitted. (Oct 2018) Awarded an Intel Faculty Grant for Research on automated performance optimization (Sep. 2018) Our paper on Foreshadow is accepted to appear at USENIX Security. 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. See www.cs.cmu.edu/~mmv/Veloso.html for her scientific publications. Second, GNNAdvisor implements a novel and highly-efficient 2D workload management tailored for GNN computation to improve GPU utilization and performance under different application settings. In this paper, we propose Oort to improve the performance of federated training and testing with guided participant selection. We propose PET, the first DNN framework that optimizes tensor programs with partially equivalent transformations and automated corrections. Forgot your password? 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. Indeed, it is a prime target for powerful adversaries such as nation states. (Jan 2019) Our REPT paper won a best paper at OSDI'18 (Oct 2018) I will serve in the SOSP'19 PC. These scripts often make pages slow to load, partly due to a fundamental inefficiency in how browsers process JavaScript content: browsers make it easy for web developers to reason about page state by serially executing all scripts on any frame in a page, but as a result, fail to leverage the multiple CPU cores that are readily available even on low-end phones. Her robot soccer teams have been RoboCup world champions several times, and the CoBot mobile robots have autonomously navigated for more than 1,000km in university buildings. These limitations require state-of-the-art systems to distribute training across multiple machines. A glance at this year's OSDI program shows that Operating Systems are a small niche topic for this conference, not even meriting their own full session. 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. We present the results of a 1% experiment at fleet scale as well as the longitudinal rollout in Googles warehouse scale computers. 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. Furthermore, such performance can be achieved without any modification in applications, network hardware, kernel CPU schedulers and/or kernel network stack. 23 artifacts received the Artifacts Functional badge (88%). 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. 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. For realistic workloads, KEVIN improves throughput by 68% on average. 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. Our approach outperforms existing file systems on a block SSD by a wide margin 6.2 on average for metadata-intensive benchmarks. 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. 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. The abstractions we design for the privacy resource mirror those defined by Kubernetes for traditional resources, but there are also major differences. 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. The chairs may reject abstracts or papers on the basis of egregious missing or extraneous conflicts. Kirk Rodrigues, Yu Luo, and Ding Yuan, University of Toronto and YScope Inc. 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 While compiler-based techniques have been proposed to improve data locality, they depend on heuristics, which can sometimes hurt performance. As a result, data characteristics and device capabilities vary widely across clients. Memory allocation represents significant compute cost at the warehouse scale and its optimization can yield considerable cost savings. We argue that a key-value interface between a file system and an SSD is superior to the legacy block interface by presenting KEVIN. In this paper, we propose a software-hardware co-design to support dynamic, fine-grained, large-scale secure memory as well as fast-initialization. USENIX new Date().getFullYear()>document.write(new Date().getFullYear()); Grants for Black Computer Science Students Application, Title Page, Copyright Page, and List of Organizers, OSDI '21 Proceedings Interior (PDF, best for mobile devices). J.P. Morgan AI Research partners with applied data analytics teams across the firm as well as with leading academic institutions globally. We introduce a hybrid cryptographic protocol for privacy-adhering transformations of encrypted data. Machine learning (ML) models trained on personal data have been shown to leak information about users. PET discovers and applies program transformations that improve computation efficiency but only maintain partial functional equivalence. Welcome to the SOSP 2021 Website. 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. PLDI seeks outstanding research that extends and/or applies programming-language concepts to advance the field of computing. Collaboration: You have a collaboration on a project, publication, grant proposal, program co-chairship, or editorship within the past two years (December 2018 through March 2021). The 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI '21) will take place as a virtual event on July 14-16, 2021. In experiments with real DL jobs and with trace-driven simulations, Pollux reduces average job completion times by 37-50% relative to state-of-the-art DL schedulers, even when they are provided with ideal resource and training configurations for every job. 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. DistAI: Data-Driven Automated Invariant Learning for Distributed Protocols Jianan Yao, Runzhou Tao, Ronghui Gu, Jason Nieh . The hybrid segment recycling chooses a proper block reclaiming policy between segment compaction and threaded logging based on their costs. Pollux is implemented and publicly available as part of an open-source project at https://github.com/petuum/adaptdl. Currently, for large graphs, CPU servers offer the best performance-per-dollar over GPU servers. How can we design systems that will be reliable despite misbehaving participants? This distinction forces a re-design of the scheduler. Academic and industrial participants present research and experience papers that cover the full range of theory and practice of computer . USENIX discourages program co-chairs from submitting papers to the conferences they organize, although they are allowed to do so. The biennial ACM Symposium on Operating Systems Principles is the world's premier forum for researchers, developers, programmers, and teachers of computer systems technology. Our evaluation shows that PET outperforms existing systems by up to 2.5, by unlocking previously missed opportunities from partially equivalent transformations. Message from the Program Co-Chairs. However, Addra improves message latency in this architecture, which is a key performance metric for voice calls. For any further information, please contact the PC chairs: [email protected]. Existing decentralized systems like Steemit, OpenBazaar, and the growing number of blockchain apps provide alternatives to existing services. Used Zotero to organize papers about the stress and diffusion between anode and electrolyte and made a summary . Haojie Wang, Jidong Zhai, Mingyu Gao, Zixuan Ma, Shizhi Tang, and Liyan Zheng, Tsinghua University; Yuanzhi Li, Carnegie Mellon University; Kaiyuan Rong and Yuanyong Chen, Tsinghua University; Zhihao Jia, Carnegie Mellon University and Facebook. 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. 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. For more details on the submission process, and for templates to use with LaTeX, Word, etc., authors should consult the detailed submission requirements. 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. Kernel code requires manual memory management and type-unsafe code and must efficiently handle complex, asynchronous events. Submission of a response is optional. Lukas Burkhalter, Nicolas Kchler, Alexander Viand, Hossein Shafagh, and Anwar Hithnawi, ETH Zrich. 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; We implemented the ZNS+ SSD at an SSD emulator and a real SSD. Authors are also encouraged to contact the program co-chairs, [email protected], if needed to relate their OSDI submissions to relevant submissions of their own that are simultaneously under review or awaiting publication at other venues. Writing a correct operating system kernel is notoriously hard. For general conference information, see https://www.usenix.org/conference/osdi22. Professor Veloso has been recognized with a multiple honors, including being a Fellow of the ACM, IEEE, AAAS, and AAAI. Cores can safely and concurrently read from their local kernel replica, eliminating remote NUMA accesses. To achieve low overhead, selective profiling gathers runtime execution information selectively and incrementally. 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. Radia Perlman is a Fellow at Dell Technologies. Papers so short as to be considered extended abstracts will not receive full consideration. 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. 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. Petuum Awarded OSDI 2021 Best Paper for Goodput-Optimized Deep Learning Research Petuum CASL research and engineering team's Pollux technical paper on adaptive scheduling for optimized. Zeph executes privacy-adhering data transformations in real-time and scales to thousands of data sources, allowing it to support large-scale low-latency data stream analytics. We have implemented a prototype of our design based on Penglai, an open-sourced enclave system for RISC-V. Questions? They collectively make the backup fresh, columnar, and fault-tolerant, even facing millions of concurrent transactions per second. Overall, the OSDI PC accepted 31 out of 165 submissions. If your paper is accepted and you need an invitation letter to apply for a visa to attend the conference, please contact [email protected] as soon as possible. Foreshadow was chosen as an IEEE Micro Top Pick. Marius is open-sourced at www.marius-project.org. 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. Existing algorithms are designed to work well for certain workloads. 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%. We also welcome work that explores the interface to related areas such as computer architecture, networking, programming languages, analytics, and databases. The 15th USENIX Symposium on Operating Systems Design and Implementation seeks to present innovative, exciting research in computer systems. 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. Unfortunately, because devices lack the semantic information about which I/O requests are latency-sensitive, these heuristics can sometimes lead to disastrous results. Using this property, MAGE calculates the memory access pattern ahead of time and uses it to produce a memory management plan. Camera-ready submission (all accepted papers): 2 April 2021; Main conference program: 27-28 April 2021; All deadline times are . To remedy this, we introduce DeSearch, the first decentralized search engine that guarantees the integrity and privacy of search results for decentralized services and blockchain apps. 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. Fluffy found two new consensus bugs in the most popular Geth Ethereum client which were exploitable on the live Ethereum mainnet. 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). Main conference program: 5-8 April 2022. Yet, existing efforts randomly select FL participants, which leads to poor model and system efficiency. While verifying GoJournal, we found one serious concurrency bug, even though GoJournal has many unit tests. The overhead of GPT is 5% for memory-intensive workloads (e.g., Redis) and negligible for CPU-intensive workloads (e.g., RV8 and Coremarks). If you have any questions about conflicts, please contact the program co-chairs. (Registered attendees: Sign in to your USENIX account to download these files. This is the first OSDI in an odd year as OSDI moves to a yearly cadence. Authors must make a good faith effort to anonymize their submissions, and they should not identify themselves or their institutions either explicitly or by implication (e.g., through the references or acknowledgments). If your accepted paper should not be published prior to the event, please notify [email protected]. The 20th ACM Workshop on Hot Topics in Networks (HotNets 2021) will bring together researchers in computer networks and systems to engage in a lively debate on the theory and practice of computer networking. 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. We present NrOS, a new OS kernel with a safer approach to synchronization that runs many POSIX programs. Graph Neural Networks (GNNs) have gained significant attention in the recent past, and become one of the fastest growing subareas in deep learning. 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. AI enables principled representation of knowledge, complex strategy optimization, learning from data, and support to human decision making. Sep 2021 - Present 1 year 7 months. 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. A graph neural network (GNN) enables deep learning on structured graph data. Uniquely, Dorylus can take advantage of serverless computing to increase scalability at a low cost. Authors may submit a response to those reviews until Friday, March 5, 2021. High-performance tensor programs are critical for efficiently deploying deep neural network (DNN) models in real-world tasks. Researchers from the Software Systems Laboratory bagged a Best Paper Award at the 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2021). 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. 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. 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. We present TEMERAIRE, a hugepage-aware enhancement of TCMALLOC to reduce CPU overheads in the applications code. Compared to existing baselines, DPF allows training more models under the same global privacy guarantee. In this paper, we show how to address this inefficiency without requiring pages to be rewritten or browsers to be modified. Dorylus is up to 3.8 faster and 10.7 cheaper compared to existing sampling-based systems. 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. We conclude with a discussion of additional techniques for improving the allocator development process and potential optimization strategies for future memory allocators. Pages should be numbered, and figures and tables should be legible in black and white, without requiring magnification. A hardware-accelerated thread scheduler makes sub-nanosecond decisions, leading to high CPU utilization and low tail response time for RPCs. 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. 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. 64 papers accepted out of 341 submitted. Welcome to the SOSP 2021 Website. Weak Links in Authentication Chains: A Large-scale Analysis of Email Sender Spoofing Attacks The copyback-aware block allocation considers different copy costs at different copy paths within the SSD. A PC member is a conflict if any of the following three circumstances applies: Institution: You are currently employed at the same institution, have been previously employed at the same institution within the past two years (not counting concluded internships), or are going to begin employment at the same institution during the review period. 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. DeSearch uses trusted hardware to build a network of workers that execute a pipeline of small search engine tasks (crawl, index, aggregate, rank, query). 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.

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