Each new model trained with DP increases the bound on data leakage and can be seen as consuming part of a global privacy budget that should not be exceeded. 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%. HotCRP.com signin Sign in using your HotCRP.com account. Authors are also encouraged to contact the program co-chairs, osdi21chairs@usenix.org, if needed to relate their OSDI submissions to relevant submissions of their own that are simultaneously under review or awaiting publication at other venues. In this paper, we propose a software-hardware co-design to support dynamic, fine-grained, large-scale secure memory as well as fast-initialization. We describe Fluffy, a multi-transaction differential fuzzer for finding consensus bugs in Ethereum. 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. Amy Tai, VMware Research; Igor Smolyar, Technion Israel Institute of Technology; Michael Wei, VMware Research; Dan Tsafrir, Technion Israel Institute of Technology and VMware Research. Paper Submission Information All submissions must be received by 11:59 PM AoE (UTC-12) on the day of the corresponding deadline. Sanitizers detect unsafe actions such as invalid memory accesses by inserting checks that are validated during a programs execution. 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. If your paper is accepted and you need an invitation letter to apply for a visa to attend the conference, please contact conference@usenix.org as soon as possible. Submitted November 12, 2021 Accepted January 20, 2022. We evaluate PrivateKube and DPF on microbenchmarks and an ML workload on Amazon Reviews data. Graph Neural Networks (GNNs) have gained significant attention in the recent past, and become one of the fastest growing subareas in deep learning. After three years working on web-based collaboration systems at a startup in North Carolina, he joined Sprint's Advanced Technology Lab in Burlingame, California, in 1998, working on cloud computing and network monitoring. Papers must be in PDF format and must be submitted via the submission form. These results outperform state-of-the-art HTAP systems by several orders of magnitude on transactional performance, while just incurring little performance slowdown (5% over pure OLTP workloads) and still enjoying data freshness for analytical queries (less than 20 ms of maximum delay) in the failure-free case. Based on this observation, P3 proposes a new approach for distributed GNN training. Radia Perlman is a Fellow at Dell Technologies. 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. Novel system designs, thorough empirical work, well-motivated theoretical results, and new application areas are all . Weak Links in Authentication Chains: A Large-scale Analysis of Email Sender Spoofing Attacks Main conference program: 5-8 April 2022. Authors are required to register abstracts by 3:00 p.m. PST on December 3, 2020, and to submit full papers by 3:00 p.m. PST on December 10, 2020. This talk will discuss several examples with very different solutions. Advisor: You have a past or present association as thesis advisor or advisee. 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 Hence, CLP enables efficient search and analytics on archived logs, something that was impossible without it. 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. MAGE outperforms the OS virtual memory system by up to an order of magnitude, and in many cases, runs SC computations that do not fit in memory at nearly the same speed as if the underlying machines had unbounded physical memory to fit the entire computation. will work with the steering committee to ensure that the symposium program will accommodate presentations for all accepted papers. 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. 1 Acknowledgements: Paper prepared for the post-conference workshop on Food for Thought: Economic Analysis in Anticipation of the Next Farm Bill at the Agricultural and Applied Economics Association annual meeting, Austin, TX . Most existing schedulers expect users to specify the number of resources for each job, often leading to inefficient resource use. A hardware-accelerated thread scheduler makes sub-nanosecond decisions, leading to high CPU utilization and low tail response time for RPCs. 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. We have implemented a prototype of our design based on Penglai, an open-sourced enclave system for RISC-V. 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. We present the results of a 1% experiment at fleet scale as well as the longitudinal rollout in Googles warehouse scale computers. 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. 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. In this talk, I'll speculate on how we came to this unfortunate state of affairs, and what might be done to fix it. 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. Paper abstracts and proceedings front matter are available to everyone now. 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. Distributed Trust: Is Blockchain the answer? Used Zotero to organize papers about the stress and diffusion between anode and electrolyte and made a summary . As the emerging trend of graph-based deep learning, Graph Neural Networks (GNNs) excel for their capability to generate high-quality node feature vectors (embeddings). 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. We observe that, due to their intended security guarantees, SC schemes are inherently oblivioustheir memory access patterns are independent of the input data. 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. NrOS replicates kernel state on each NUMA node and uses operation logs to maintain strong consistency between replicas. 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. 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). Moreover, to handle dynamic workloads, Nap adopts a fast NAL switch mechanism. 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. SC is being increasingly adopted by industry for a variety of applications. We propose a learning-based framework that instead explicitly optimizes concurrency control via offline training to maximize performance. The device then "calibrates" its interrupts to completions of latency-sensitive requests. Accepted papers will be allowed 14 pages in the proceedings, plus references. Currently, for large graphs, CPU servers offer the best performance-per-dollar over GPU servers. Swapnil Gandhi and Anand Padmanabha Iyer, Microsoft Research. Call for Papers. Overall, the OSDI PC accepted 31 out of 165 submissions. In some cases, the quality of these artifacts is as important as that of the document itself. Unfortunately, because devices lack the semantic information about which I/O requests are latency-sensitive, these heuristics can sometimes lead to disastrous results. Existing frameworks optimize tensor programs by applying fully equivalent transformations, which maintain equivalence on every element of output tensors. Fan Lai, Xiangfeng Zhu, Harsha V. Madhyastha, and Mosharaf Chowdhury, University of Michigan. 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. This paper presents Dorylus: a distributed system for training GNNs. 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. Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, and Yufei Ding, University of California, Santa Barbara. We conclude with a discussion of additional techniques for improving the allocator development process and potential optimization strategies for future memory allocators. If the conference registration fee will pose a hardship for the presenter of the accepted paper, please contact conference@usenix.org. The OSDI '21 program co-chairs have agreed not to submit their work to OSDI '21. 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.
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