Greenwell School Gateshead, Richest Cities In Ecuador, Can Gerbils Eat Dried Cranberries, Nvidia Sydney Office Address, Brad Heller Age, Articles O

Message from the Program Co-Chairs. Welcome to the 2021 USENIX Annual Technical Conference (ATC '21) submissions site! 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. Lukas Burkhalter, Nicolas Kchler, Alexander Viand, Hossein Shafagh, and Anwar Hithnawi, ETH Zrich. We propose PET, the first DNN framework that optimizes tensor programs with partially equivalent transformations and automated corrections. OSDI takes a broad view of the systems area and solicits contributions from many fields of systems practice, including, but not limited to, operating systems, file and storage systems, distributed systems, cloud computing, mobile systems, secure and reliable systems, systems aspects of big data, embedded systems, virtualization, networking as it relates to operating systems, and management and troubleshooting of complex systems. 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. JEL codes: Q18, Q28, Q57 . In this paper, we propose a software-hardware co-design to support dynamic, fine-grained, large-scale secure memory as well as fast-initialization. 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. 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. Welcome to the 2021 USENIX Annual Technical Conference (ATC '21) submissions site! We present Nap, a black-box approach that converts concurrent persistent memory (PM) indexes into NUMA-aware counterparts. As has been standard practice in OSDI and SOSP in recent years, we will allow authors to submit quick responses to PC reviews: they will be made available to the PC before the final online discussion and PC meeting. ), Program Co-Chairs: Angela Demke Brown, University of Toronto, and Jay Lorch, Microsoft Research. We discuss the design and implementation of TEMERAIRE including strategies for hugepage-aware memory layouts to maximize hugepage coverage and to minimize fragmentation overheads. OSDI will provide an opportunity for authors to respond to reviews prior to final consideration of the papers at the program committee meeting. The overhead of GPT is 5% for memory-intensive workloads (e.g., Redis) and negligible for CPU-intensive workloads (e.g., RV8 and Coremarks). We compare Marius against two state-of-the-art industrial systems on a diverse array of benchmarks. 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. 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. DeSearch uses trusted hardware to build a network of workers that execute a pipeline of small search engine tasks (crawl, index, aggregate, rank, query). 23 artifacts received the Artifacts Functional badge (88%). 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. Graph Neural Networks (GNNs) have gained significant attention in the recent past, and become one of the fastest growing subareas in deep learning. Metadata from voice calls, such as the knowledge of who is communicating with whom, contains rich information about peoples lives. To this end, we propose GNNAdvisor, an adaptive and efficient runtime system to accelerate various GNN workloads on GPU platforms. Such centralized engines are in a perfect position to censor content and violate users privacy, undermining some of the key tenets behind decentralization. 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. Yet, existing efforts randomly select FL participants, which leads to poor model and system efficiency. To achieve low overhead, selective profiling gathers runtime execution information selectively and incrementally. 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. This paper presents Dorylus: a distributed system for training GNNs. Proceedings Front Matter The symposium emphasizes innovative research as well as quantified or insightful experiences in systems design and implementation. 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. Submission of a response is optional. Author Response 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. 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. Last year, 70% of accepted OSDI papers participated in the . 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). 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. 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. 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. She developed the technology for making network routing self-stabilizing, largely self-managing, and scalable. Research Impact Score 9.24. . PLDI is a premier forum for programming language research, broadly construed, including design, implementation, theory, applications, and performance. Pollux simultaneously considers both aspects. OSDI 2021 papers summary. Papers must be in PDF format and must be submitted via the submission form. Welcome to the SOSP 2021 Website. 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. 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. Researchers from the Software Systems Laboratory bagged a Best Paper Award at the 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2021). Title Page, Copyright Page, and List of Organizers | 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. 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. Qing Wang, Youyou Lu, Junru Li, and Jiwu Shu, Tsinghua University. 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. Secure Computation (SC) is a family of cryptographic primitives for computing on encrypted data in single-party and multi-party settings. She also invented the spanning tree algorithm, which transformed Ethernet from a technology that supported a few hundred nodes, to something that can support large networks. Responses should be limited to clarifying the submitted work. In addition, increasing CPU core counts further complicate kernel development. To enable FL developers to interpret their results in model testing, Oort enforces their requirements on the distribution of participant data while improving the duration of federated testing by cherry-picking clients. A.H. Hunter, Jane Street Capital; Chris Kennelly, Paul Turner, Darryl Gove, Tipp Moseley, and Parthasarathy Ranganathan, Google. 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. In 2023 I started another two-year term on the . 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. 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. Professor Veloso earned a Bachelor and Master of Science degrees in Electrical and Computer Engineering from Instituto Superior Tecnico in Lisbon, Portugal, a Master of Arts in Computer Science from Boston University, and Master of Science and PhD in Computer Science from Carnegie Mellon University. Despite having the same end goals as traditional ML, FL executions differ significantly in scale, spanning thousands to millions of participating devices. Federated Learning (FL) is an emerging direction in distributed machine learning (ML) that enables in-situ model training and testing on edge data. 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. Kernel code requires manual memory management and type-unsafe code and must efficiently handle complex, asynchronous events. The OSDI Symposium emphasizes innovative research as well as quantified or insightful experiences in systems design and implementation. OSDI brings together professionals from academic and industrial backgrounds in a premier forum for discussing the design, implementation, and implications of systems software. This is especially true for DPF over Rnyi DP, a highly composable form of DP. The NAL eliminates remote PM accesses to hot items without inducing extra local PM accesses. Shaghayegh Mardani, UCLA; Ayush Goel, University of Michigan; Ronny Ko, Harvard University; Harsha V. Madhyastha, University of Michigan; Ravi Netravali, Princeton University. We build Polyjuice based on our learning framework and evaluate it against several existing algorithms. 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. Zeph enforces privacy policies cryptographically and ensures that data available to third-party applications complies with users' privacy policies. 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. Authors of each accepted paper must ensure that at least one author registers for the conference, and that their paper is presented in-person at the conference. 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; 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. A significant obstacle to using SC for practical applications is the memory overhead of the underlying cryptography. GoJournals goal is to bring the advantages of journaling for code to specs and proofs. Based on this observation, P3 proposes a new approach for distributed GNN training. As a result, data characteristics and device capabilities vary widely across clients. 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. 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. To adapt to different workloads, prior works mix or switch between a few known algorithms using manual insights or simple heuristics. 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. Although SSDs can be simplified under the current ZNS interface, its counterpart LFS must bear segment compaction overhead. 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. We argue that a key-value interface between a file system and an SSD is superior to the legacy block interface by presenting KEVIN. Sat, Aug 7, 2021 3 min read researches review. Consensus bugs are bugs that make Ethereum clients transition to incorrect blockchain states and fail to reach consensus with other clients. 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. 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 Conference site 49 papers accepted out of 251 submitted. The 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI '21) will take place as a virtual event on July 1416, 2021. Welcome to the SOSP 2021 Website. In this talk, I'll speculate on how we came to this unfortunate state of affairs, and what might be done to fix it. 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). She is the author of the textbook Interconnections (about network layers 2 and 3) and coauthor of Network Security. When registering your abstract, you must provide information about conflicts with PC members. Second, it innovates on the underlying cryptographic machinery and constructs a new private information retrieval scheme, FastPIR, that reduces the time to process oblivious access requests for mailboxes. 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. 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. HotNets provides a venue for discussing innovative ideas and for debating future research agendas in networking. 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. Jaehyun Hwang and Midhul Vuppalapati, Cornell University; Simon Peter, UT Austin; Rachit Agarwal, Cornell University. We present the results of a 1% experiment at fleet scale as well as the longitudinal rollout in Googles warehouse scale computers. We present DistAI, a data-driven automated system for learning inductive invariants for distributed protocols. Questions? We demonstrate that KEVIN reduces the amount of I/O traffic between the host and the device, and remains particularly robust as the system ages and the data become fragmented. To evaluate the security guarantees of Storm, we build a formally verified reference implementation using the Labeled IO (LIO) IFC framework. For conference information, . This year, there were only 2 accepted papers from UK institutes. 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. Fluffy found two new consensus bugs in the most popular Geth Ethereum client which were exploitable on the live Ethereum mainnet. (Visa applications can take at least 30 working days to process.) 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. 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. 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%). Swapnil Gandhi and Anand Padmanabha Iyer, Microsoft Research. 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% (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. 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. Papers not meeting these criteria will be rejected without review, and no deadline extensions will be granted for reformatting. Storm ensures security using a Security Typed ORM that refines the (type) abstractions of each layer of the MVC API with logical assertions that describe the data produced and consumed by the underlying operation and the users allowed access to that data. 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 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. 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). These limitations require state-of-the-art systems to distribute training across multiple machines. (Registered attendees: Sign in to your USENIX account to download these files. All the times listed below are in Pacific Daylight Time (PDT). 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. 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. The NVMe zoned namespace (ZNS) is emerging as a new storage interface, where the logical address space is divided into fixed-sized zones, and each zone must be written sequentially for flash-memory-friendly access. Tao Luo, Mingen Pan, Pierre Tholoniat, Asaf Cidon, and Roxana Geambasu, Columbia University; Mathias Lcuyer, Microsoft Research. 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. In addition, CLP outperforms Elasticsearch and Splunk Enterprise's log ingestion performance by over 13x, and we show CLP scales to petabytes of logs. To help more profitably utilize sanitizers, we introduce SanRazor, a practical tool aiming to effectively detect and remove redundant sanitizer checks. Of the 26 submitted artifacts: 26 artifacts received the Artifacts Available badge (100%). For realistic workloads, KEVIN improves throughput by 68% on average. Notification of conditional accept/reject for revisions: 3 March 2022. 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. One classical approach is to increase the efficiency of an allocator to minimize the cycles spent in the allocator code. As a member of ACCT, I have served two years on the bylaws and governance committee and two years on the finance and audit committee. 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. DistAI generates data by simulating the distributed protocol at different instance sizes and recording states as samples. We demonstrate that Marius achieves the same level of accuracy but is up to one order of magnitude faster. If the conference registration fee will pose a hardship for the presenter of the accepted paper, please contact conference@usenix.org. 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. 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. A graph neural network (GNN) enables deep learning on structured graph data. Tej Chajed, MIT CSAIL; Joseph Tassarotti, Boston College; Mark Theng, MIT CSAIL; Ralf Jung, MPI-SWS; M. Frans Kaashoek and Nickolai Zeldovich, MIT CSAIL. We describe Fluffy, a multi-transaction differential fuzzer for finding consensus bugs in Ethereum. She also has made contributions in network security, including scalable data expiration, distributed algorithms despite malicious participants, and DDOS prevention techniques. We also verified a simple NFS server using GoJournals specs, which confirms that they are helpful for application verification: a significant part of the proof doesnt have to consider concurrency and crashes. 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. 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. This kernel is scaled across NUMA nodes using node replication, a scheme inspired by state machine replication in distributed systems. 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. Secure hardware enclaves have been widely used for protecting security-critical applications in the cloud. PLDI seeks outstanding research that extends and/or applies programming-language concepts to advance the field of computing. Forgot your password? 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.