osdi 2021 accepted papers

For example, talks may be shorter than in prior years, or some parts of the conference may be multi-tracked. In 2023 I started another two-year term on the . 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. We also welcome work that explores the interface to related areas such as computer architecture, networking, programming languages, analytics, and databases. We present application studies for 8 applications, improving requests-per-second (RPS) by 7.7% and reducing RAM usage 2.4%. Camera-ready submission (all accepted papers): 2 April 2021; Main conference program: 27-28 April 2021; All deadline times are . 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. 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. 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%). This formulation of memory management, which we call memory programming, is a generalization of paging that allows MAGE to provide a highly efficient virtual memory abstraction for SC. 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. Authors may submit a response to those reviews until Friday, March 5, 2021. Editor in charge: Daniel Petrolia . 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. Accepted papers will be allowed 14 pages in the proceedings, plus references. The key to our solution, Horcrux, is to account for the non-determinism intrinsic to web page loads and the constraints placed by the browsers API for parallelism. 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. USENIX Security '21 has three submission deadlines. The co-chairs may then share that paper with the workshops organizers and discuss it with them. Conference site 49 papers accepted out of 251 submitted. 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). 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. 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. Lukas Burkhalter, Nicolas Kchler, Alexander Viand, Hossein Shafagh, and Anwar Hithnawi, ETH Zrich. We demonstrate that the hardware thread scheduler is able to lower RPC tail response time by about 5 while enabling the system to sustain 20% higher load, relative to traditional thread scheduling techniques. This paper describes the design, implementation, and evaluation of Addra, the first system for voice communication that hides metadata over fully untrusted infrastructure and scales to tens of thousands of users. We prove that DistAI is guaranteed to find the -free inductive invariant that proves the desired safety properties in finite time, if one exists. We present the results of a 1% experiment at fleet scale as well as the longitudinal rollout in Googles warehouse scale computers. Devices employ adaptive interrupt coalescing heuristics that try to balance between these opposing goals. This motivates the need for a new approach to data privacy that can provide strong assurance and control to users. Papers accompanied by nondisclosure agreement forms will not be considered. 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 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. Sat, Aug 7, 2021 3 min read researches review. (Registered attendees: Sign in to your USENIX account to download these files. 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. 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. In the Ethereum network, decentralized Ethereum clients reach consensus through transitioning to the same blockchain states according to the Ethereum specification. Currently, for large graphs, CPU servers offer the best performance-per-dollar over GPU servers. AI enables principled representation of knowledge, complex strategy optimization, learning from data, and support to human decision making. 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. Advisor: You have a past or present association as thesis advisor or advisee. She is the author of the textbook Interconnections (about network layers 2 and 3) and coauthor of Network Security. 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. Existing algorithms are designed to work well for certain workloads. Research Impact Score 9.24. . Performance experiments show that GoNFS provides similar performance (e.g., at least 90% throughput across several benchmarks on an NVMe disk) to Linuxs NFS server exporting an ext4 file system, suggesting that GoJournal is a competitive journaling system. Here, we focus on hugepage coverage. Our further evaluation on 38 CVEs from 10 commonly-used programs shows that SanRazor reduced checks suffice to detect at least 33 out of the 38 CVEs. We present DistAI, a data-driven automated system for learning inductive invariants for distributed protocols. 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. Prior or concurrent publication in non-peer-reviewed contexts, like arXiv.org, technical reports, talks, and social media posts, is permitted. In this paper, we present P3, a system that focuses on scaling GNN model training to large real-world graphs in a distributed setting. A hardware-accelerated thread scheduler makes sub-nanosecond decisions, leading to high CPU utilization and low tail response time for RPCs. 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. (Visa applications can take at least 30 working days to process.) Submitted November 12, 2021 Accepted January 20, 2022. DistAI generates data by simulating the distributed protocol at different instance sizes and recording states as samples. Existing decentralized systems like Steemit, OpenBazaar, and the growing number of blockchain apps provide alternatives to existing services. 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. To help more profitably utilize sanitizers, we introduce SanRazor, a practical tool aiming to effectively detect and remove redundant sanitizer checks. We evaluate PrivateKube and DPF on microbenchmarks and an ML workload on Amazon Reviews data. Shaghayegh Mardani, UCLA; Ayush Goel, University of Michigan; Ronny Ko, Harvard University; Harsha V. Madhyastha, University of Michigan; Ravi Netravali, Princeton University. 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. Concurrency control algorithms are key determinants of the performance of in-memory databases. The biennial ACM Symposium on Operating Systems Principles is the world's premier forum for researchers, developers, programmers, and teachers of computer systems technology. 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. Pages should be numbered, and figures and tables should be legible in black and white, without requiring magnification. Welcome to the 2021 USENIX Annual Technical Conference (ATC '21) submissions site! (Jan 2019) Our REPT paper won a best paper at OSDI'18 (Oct 2018) I will serve in the SOSP'19 PC. 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. 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. Please identify yourself as a presenter and include your mailing address in your email. Message from the Program Co-Chairs. 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. 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. We propose a new framework for computing the embeddings of large-scale graphs on a single machine. Further, Vegito can recover from cascading machine failures by using the columnar backup in less than 60 ms. Memory allocation represents significant compute cost at the warehouse scale and its optimization can yield considerable cost savings. 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. Pollux simultaneously considers both aspects. 2019 - Present. 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. J.P. Morgan AI Research partners with applied data analytics teams across the firm as well as with leading academic institutions globally. 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; This post is for recording some notes from a few OSDI'21 papers that I got fun. At a high level, Addra follows a template in which callers and callees deposit and retrieve messages from private mailboxes hosted at an untrusted server. This yielded 6% fewer TLB miss stalls, and 26% reduction in memory wasted due to fragmentation. Prior or concurrent workshop publication does not preclude publishing a related paper in OSDI. 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. Welcome to the SOSP 2021 Website. One classical approach is to increase the efficiency of an allocator to minimize the cycles spent in the allocator code. In this talk, I'll speculate on how we came to this unfortunate state of affairs, and what might be done to fix it. Instead of choosing among a small number of known algorithms, our approach searches in a "policy space" of fine-grained actions, resulting in novel algorithms that can outperform existing algorithms by specializing to a given workload. 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. 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). 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. KEVIN combines a fast, lightweight, and POSIX compliant file system with a key-value storage device that performs in-storage indexing. 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. We implement a variant of a log-structured merge tree in the storage device that not only indexes file objects, but also supports transactions and manages physical storage space. SC is being increasingly adopted by industry for a variety of applications. Using this property, MAGE calculates the memory access pattern ahead of time and uses it to produce a memory management plan. Compared to existing baselines, DPF allows training more models under the same global privacy guarantee. Contact your program co-chairs, osdi21chairs@usenix.org, or the USENIX office, submissionspolicy@usenix.org. The paper review process is double-blind. And yet, they continue to rely on centralized search engines and indexers to help users access the content they seek and navigate the apps. 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. Sijie Shen, Rong Chen, Haibo Chen, and Binyu Zang, Institute of Parallel and Distributed Systems, Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory; Engineering Research Center for Domain-specific Operating Systems, Ministry of Education, China.

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