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name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2411.02814">arXiv:2411.02814</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2411.02814">pdf</a>, <a href="https://arxiv.org/format/2411.02814">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Performance">cs.PF</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Hardware Architecture">cs.AR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Operating Systems">cs.OS</span> </div> </div> <p class="title is-5 mathjax"> The Hitchhiker&#39;s Guide to Programming and Optimizing CXL-Based Heterogeneous Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Wang%2C+Z">Zixuan Wang</a>, <a href="/search/cs?searchtype=author&amp;query=Mahar%2C+S">Suyash Mahar</a>, <a href="/search/cs?searchtype=author&amp;query=Li%2C+L">Luyi Li</a>, <a href="/search/cs?searchtype=author&amp;query=Park%2C+J">Jangseon Park</a>, <a href="/search/cs?searchtype=author&amp;query=Kim%2C+J">Jinpyo Kim</a>, <a href="/search/cs?searchtype=author&amp;query=Michailidis%2C+T">Theodore Michailidis</a>, <a href="/search/cs?searchtype=author&amp;query=Pan%2C+Y">Yue Pan</a>, <a href="/search/cs?searchtype=author&amp;query=Rosing%2C+T">Tajana Rosing</a>, <a href="/search/cs?searchtype=author&amp;query=Tullsen%2C+D">Dean Tullsen</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a>, <a href="/search/cs?searchtype=author&amp;query=Ryoo%2C+K+C">Kyung Chang Ryoo</a>, <a href="/search/cs?searchtype=author&amp;query=Park%2C+S">Sungjoo Park</a>, <a href="/search/cs?searchtype=author&amp;query=Zhao%2C+J">Jishen Zhao</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2411.02814v1-abstract-short" style="display: inline;"> We present a thorough analysis of the use of CXL-based heterogeneous systems. We built a cluster of server systems that combines different vendor&#39;s CPUs and various types of CXL devices. We further developed a heterogeneous memory benchmark suite, Heimdall, to profile the performance of such heterogeneous systems. By leveraging Heimdall, we unveiled the detailed architecture design in these system&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02814v1-abstract-full').style.display = 'inline'; document.getElementById('2411.02814v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2411.02814v1-abstract-full" style="display: none;"> We present a thorough analysis of the use of CXL-based heterogeneous systems. We built a cluster of server systems that combines different vendor&#39;s CPUs and various types of CXL devices. We further developed a heterogeneous memory benchmark suite, Heimdall, to profile the performance of such heterogeneous systems. By leveraging Heimdall, we unveiled the detailed architecture design in these systems, drew observations on optimizing performance for workloads, and pointed out directions for future development of CXL-based heterogeneous systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2411.02814v1-abstract-full').style.display = 'none'; document.getElementById('2411.02814v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 November, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2408.11325">arXiv:2408.11325</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2408.11325">pdf</a>, <a href="https://arxiv.org/format/2408.11325">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Operating Systems">cs.OS</span> </div> </div> <p class="title is-5 mathjax"> Telepathic Datacenters: Fast RPCs using Shared CXL Memory </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Mahar%2C+S">Suyash Mahar</a>, <a href="/search/cs?searchtype=author&amp;query=Hajyjasini%2C+E">Ehsan Hajyjasini</a>, <a href="/search/cs?searchtype=author&amp;query=Lee%2C+S">Seungjin Lee</a>, <a href="/search/cs?searchtype=author&amp;query=Zhang%2C+Z">Zifeng Zhang</a>, <a href="/search/cs?searchtype=author&amp;query=Shen%2C+M">Mingyao Shen</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2408.11325v1-abstract-short" style="display: inline;"> Datacenter applications often rely on remote procedure calls (RPCs) for fast, efficient, and secure communication. However, RPCs are slow, inefficient, and hard to use as they require expensive serialization and compression to communicate over a packetized serial network link. Compute Express Link 3.0 (CXL) offers an alternative solution, allowing applications to share data using a cache-coherent,&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.11325v1-abstract-full').style.display = 'inline'; document.getElementById('2408.11325v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2408.11325v1-abstract-full" style="display: none;"> Datacenter applications often rely on remote procedure calls (RPCs) for fast, efficient, and secure communication. However, RPCs are slow, inefficient, and hard to use as they require expensive serialization and compression to communicate over a packetized serial network link. Compute Express Link 3.0 (CXL) offers an alternative solution, allowing applications to share data using a cache-coherent, shared-memory interface across clusters of machines. RPCool is a new framework that exploits CXL&#39;s shared memory capabilities. RPCool avoids serialization by passing pointers to data structures in shared memory. While avoiding serialization is useful, directly sharing pointer-rich data eliminates the isolation that copying data over traditional networks provides, leaving the receiver vulnerable to invalid pointers and concurrent updates to shared data by the sender. RPCool restores this safety with careful and efficient management of memory permissions. Another significant challenge with CXL shared memory capabilities is that they are unlikely to scale to an entire datacenter. RPCool addresses this by falling back to RDMA-based communication. Overall, RPCool reduces the round-trip latency by 1.93$\times$ and 7.2$\times$ compared to state-of-the-art RDMA and CXL-based RPC mechanisms, respectively. Moreover, RPCool performs either comparably or better than other RPC mechanisms across a range of workloads. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.11325v1-abstract-full').style.display = 'none'; document.getElementById('2408.11325v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 August, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.19626">arXiv:2405.19626</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2405.19626">pdf</a>, <a href="https://arxiv.org/format/2405.19626">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> </div> </div> <p class="title is-5 mathjax"> CXL Shared Memory Programming: Barely Distributed and Almost Persistent </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Xu%2C+Y">Yi Xu</a>, <a href="/search/cs?searchtype=author&amp;query=Mahar%2C+S">Suyash Mahar</a>, <a href="/search/cs?searchtype=author&amp;query=Liu%2C+Z">Ziheng Liu</a>, <a href="/search/cs?searchtype=author&amp;query=Shen%2C+M">Mingyao Shen</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2405.19626v2-abstract-short" style="display: inline;"> While Compute Express Link (CXL) enables support for cache-coherent shared memory among multiple nodes, it also introduces new types of failures--processes can fail before data does, or data might fail before a process does. The lack of a failure model for CXL-based shared memory makes it challenging to understand and mitigate these failures. To solve these challenges, in this paper, we describe&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.19626v2-abstract-full').style.display = 'inline'; document.getElementById('2405.19626v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.19626v2-abstract-full" style="display: none;"> While Compute Express Link (CXL) enables support for cache-coherent shared memory among multiple nodes, it also introduces new types of failures--processes can fail before data does, or data might fail before a process does. The lack of a failure model for CXL-based shared memory makes it challenging to understand and mitigate these failures. To solve these challenges, in this paper, we describe a model categorizing and handling the CXL-based shared memory&#39;s failures: data and process failures. Data failures in CXL-based shared memory render data inaccessible or inconsistent for a currently running application. We argue that such failures are unlike data failures in distributed storage systems and require CXL-specific handling. To address this, we look into traditional data failure mitigation techniques like erasure coding and replication and propose new solutions to better handle data failures in CXL-based shared memory systems. Next, we look into process failures and compare the failures and potential solutions with PMEM&#39;s failure model and programming solutions. We argue that although PMEM shares some of CXL&#39;s characteristics, it does not fully address CXL&#39;s volatile nature and low access latencies. Finally, taking inspiration from PMEM programming solutions, we propose techniques to handle these new failures. Thus, this paper is the first work to define the CXL-based shared memory failure model and propose tailored solutions that address challenges specific to CXL-based systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.19626v2-abstract-full').style.display = 'none'; document.getElementById('2405.19626v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 29 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2403.18537">arXiv:2403.18537</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2403.18537">pdf</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Logic in Computer Science">cs.LO</span> </div> </div> <p class="title is-5 mathjax"> A Path Towards Legal Autonomy: An interoperable and explainable approach to extracting, transforming, loading and computing legal information using large language models, expert systems and Bayesian networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Constant%2C+A">Axel Constant</a>, <a href="/search/cs?searchtype=author&amp;query=Westermann%2C+H">Hannes Westermann</a>, <a href="/search/cs?searchtype=author&amp;query=Wilson%2C+B">Bryan Wilson</a>, <a href="/search/cs?searchtype=author&amp;query=Kiefer%2C+A">Alex Kiefer</a>, <a href="/search/cs?searchtype=author&amp;query=Hipolito%2C+I">Ines Hipolito</a>, <a href="/search/cs?searchtype=author&amp;query=Pronovost%2C+S">Sylvain Pronovost</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a>, <a href="/search/cs?searchtype=author&amp;query=Albarracin%2C+M">Mahault Albarracin</a>, <a href="/search/cs?searchtype=author&amp;query=Ramstead%2C+M+J+D">Maxwell J. D. Ramstead</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2403.18537v1-abstract-short" style="display: inline;"> Legal autonomy - the lawful activity of artificial intelligence agents - can be achieved in one of two ways. It can be achieved either by imposing constraints on AI actors such as developers, deployers and users, and on AI resources such as data, or by imposing constraints on the range and scope of the impact that AI agents can have on the environment. The latter approach involves encoding extant&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.18537v1-abstract-full').style.display = 'inline'; document.getElementById('2403.18537v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2403.18537v1-abstract-full" style="display: none;"> Legal autonomy - the lawful activity of artificial intelligence agents - can be achieved in one of two ways. It can be achieved either by imposing constraints on AI actors such as developers, deployers and users, and on AI resources such as data, or by imposing constraints on the range and scope of the impact that AI agents can have on the environment. The latter approach involves encoding extant rules concerning AI driven devices into the software of AI agents controlling those devices (e.g., encoding rules about limitations on zones of operations into the agent software of an autonomous drone device). This is a challenge since the effectivity of such an approach requires a method of extracting, loading, transforming and computing legal information that would be both explainable and legally interoperable, and that would enable AI agents to reason about the law. In this paper, we sketch a proof of principle for such a method using large language models (LLMs), expert legal systems known as legal decision paths, and Bayesian networks. We then show how the proposed method could be applied to extant regulation in matters of autonomous cars, such as the California Vehicle Code. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.18537v1-abstract-full').style.display = 'none'; document.getElementById('2403.18537v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 March, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2310.16300">arXiv:2310.16300</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2310.16300">pdf</a>, <a href="https://arxiv.org/format/2310.16300">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Operating Systems">cs.OS</span> </div> </div> <p class="title is-5 mathjax"> Snapshot: Fast, Userspace Crash Consistency for CXL and PM Using msync </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Mahar%2C+S">Suyash Mahar</a>, <a href="/search/cs?searchtype=author&amp;query=Shen%2C+M">Mingyao Shen</a>, <a href="/search/cs?searchtype=author&amp;query=Kelly%2C+T">Terence Kelly</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2310.16300v1-abstract-short" style="display: inline;"> Crash consistency using persistent memory programming libraries requires programmers to use complex transactions and manual annotations. In contrast, the failure-atomic msync() (FAMS) interface is much simpler as it transparently tracks updates and guarantees that modified data is atomically durable on a call to the failure-atomic variant of msync(). However, FAMS suffers from several drawbacks, l&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.16300v1-abstract-full').style.display = 'inline'; document.getElementById('2310.16300v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2310.16300v1-abstract-full" style="display: none;"> Crash consistency using persistent memory programming libraries requires programmers to use complex transactions and manual annotations. In contrast, the failure-atomic msync() (FAMS) interface is much simpler as it transparently tracks updates and guarantees that modified data is atomically durable on a call to the failure-atomic variant of msync(). However, FAMS suffers from several drawbacks, like the overhead of msync() and the write amplification from page-level dirty data tracking. To address these drawbacks while preserving the advantages of FAMS, we propose Snapshot, an efficient userspace implementation of FAMS. Snapshot uses compiler-based annotation to transparently track updates in userspace and syncs them with the backing byte-addressable storage copy on a call to msync(). By keeping a copy of application data in DRAM, Snapshot improves access latency. Moreover, with automatic tracking and syncing changes only on a call to msync(), Snapshot provides crash-consistency guarantees, unlike the POSIX msync() system call. For a KV-Store backed by Intel Optane running the YCSB benchmark, Snapshot achieves at least 1.2$\times$ speedup over PMDK while significantly outperforming conventional (non-crash-consistent) msync(). On an emulated CXL memory semantic SSD, Snapshot outperforms PMDK by up to 10.9$\times$ on all but one YCSB workload, where PMDK is 1.2$\times$ faster than Snapshot. Further, Kyoto Cabinet commits perform up to 8.0$\times$ faster with Snapshot than its built-in, msync()-based crash-consistency mechanism. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.16300v1-abstract-full').style.display = 'none'; document.getElementById('2310.16300v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 October, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">A shorter version of this paper appeared in the Proceedings of ICCD 2023</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2310.02183">arXiv:2310.02183</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2310.02183">pdf</a>, <a href="https://arxiv.org/format/2310.02183">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> </div> </div> <p class="title is-5 mathjax"> Puddles: Application-Independent Recovery and Location-Independent Data for Persistent Memory </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Mahar%2C+S">Suyash Mahar</a>, <a href="/search/cs?searchtype=author&amp;query=Shen%2C+M">Mingyao Shen</a>, <a href="/search/cs?searchtype=author&amp;query=Smith%2C+T">TJ Smith</a>, <a href="/search/cs?searchtype=author&amp;query=Izraelevitz%2C+J">Joseph Izraelevitz</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2310.02183v1-abstract-short" style="display: inline;"> In this paper, we argue that current work has failed to provide a comprehensive and maintainable in-memory representation for persistent memory. PM data should be easily mappable into a process address space, shareable across processes, shippable between machines, consistent after a crash, and accessible to legacy code with fast, efficient pointers as first-class abstractions. While existing s&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.02183v1-abstract-full').style.display = 'inline'; document.getElementById('2310.02183v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2310.02183v1-abstract-full" style="display: none;"> In this paper, we argue that current work has failed to provide a comprehensive and maintainable in-memory representation for persistent memory. PM data should be easily mappable into a process address space, shareable across processes, shippable between machines, consistent after a crash, and accessible to legacy code with fast, efficient pointers as first-class abstractions. While existing systems have provided niceties like mmap()-based load/store access, they have not been able to support all these necessary properties due to conflicting requirements. We propose Puddles, a new persistent memory abstraction, to solve these problems. Puddles provide application-independent recovery after a power outage; they make recovery from a system failure a system-level property of the stored data rather than the responsibility of the programs that access it. Puddles use native pointers, so they are compatible with existing code. Finally, Puddles implement support for sharing and shipping of PM data between processes and systems without expensive serialization and deserialization. Compared to existing systems, Puddles are at least as fast as and up to 1.34$\times$ faster than PMDK while being competitive with other PM libraries across YCSB workloads. Moreover, to demonstrate Puddles&#39; ability to relocate data, we showcase a sensor network data-aggregation workload that results in a 4.7$\times$ speedup over PMDK. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2310.02183v1-abstract-full').style.display = 'none'; document.getElementById('2310.02183v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 October, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">To appear in EuroSys 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.06620">arXiv:2303.06620</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2303.06620">pdf</a>, <a href="https://arxiv.org/format/2303.06620">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> PCB-ready breakout boards: Bridging the gap between electronics prototyping and production </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Garza%2C+J">J. Garza</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.06620v2-abstract-short" style="display: inline;"> Electronics prototyping using breakout boards allows designers with and without an engineering background to rapidly create interactive prototypes. However, when it comes to transition to a production-ready PCB design, stagnation exists due to the high skill floor required for PCB design. While PCB design automation has been used successfully in recent research tools to reduce the required experti&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.06620v2-abstract-full').style.display = 'inline'; document.getElementById('2303.06620v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.06620v2-abstract-full" style="display: none;"> Electronics prototyping using breakout boards allows designers with and without an engineering background to rapidly create interactive prototypes. However, when it comes to transition to a production-ready PCB design, stagnation exists due to the high skill floor required for PCB design. While PCB design automation has been used successfully in recent research tools to reduce the required expertise, little has been done to integrate these tools directly into the electronics prototyping cycle. This position paper aims to bring attention to the possibility of integrating recent PCB design automation paradigms into the electronics prototyping cycle for the creation of PCB-ready breakout boards: breakout boards whose designs would have the ability to be pipelined directly into new user interfaces that leverage the use of automation for the rapid creation of production-ready PCB designs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.06620v2-abstract-full').style.display = 'none'; document.getElementById('2303.06620v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 12 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2212.01354">arXiv:2212.01354</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2212.01354">pdf</a>, <a href="https://arxiv.org/format/2212.01354">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Multiagent Systems">cs.MA</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Adaptation and Self-Organizing Systems">nlin.AO</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1177/26339137231222481">10.1177/26339137231222481 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Designing Ecosystems of Intelligence from First Principles </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Friston%2C+K+J">Karl J Friston</a>, <a href="/search/cs?searchtype=author&amp;query=Ramstead%2C+M+J+D">Maxwell J D Ramstead</a>, <a href="/search/cs?searchtype=author&amp;query=Kiefer%2C+A+B">Alex B Kiefer</a>, <a href="/search/cs?searchtype=author&amp;query=Tschantz%2C+A">Alexander Tschantz</a>, <a href="/search/cs?searchtype=author&amp;query=Buckley%2C+C+L">Christopher L Buckley</a>, <a href="/search/cs?searchtype=author&amp;query=Albarracin%2C+M">Mahault Albarracin</a>, <a href="/search/cs?searchtype=author&amp;query=Pitliya%2C+R+J">Riddhi J Pitliya</a>, <a href="/search/cs?searchtype=author&amp;query=Heins%2C+C">Conor Heins</a>, <a href="/search/cs?searchtype=author&amp;query=Klein%2C+B">Brennan Klein</a>, <a href="/search/cs?searchtype=author&amp;query=Millidge%2C+B">Beren Millidge</a>, <a href="/search/cs?searchtype=author&amp;query=Sakthivadivel%2C+D+A+R">Dalton A R Sakthivadivel</a>, <a href="/search/cs?searchtype=author&amp;query=Smithe%2C+T+S+C">Toby St Clere Smithe</a>, <a href="/search/cs?searchtype=author&amp;query=Koudahl%2C+M">Magnus Koudahl</a>, <a href="/search/cs?searchtype=author&amp;query=Tremblay%2C+S+E">Safae Essafi Tremblay</a>, <a href="/search/cs?searchtype=author&amp;query=Petersen%2C+C">Capm Petersen</a>, <a href="/search/cs?searchtype=author&amp;query=Fung%2C+K">Kaiser Fung</a>, <a href="/search/cs?searchtype=author&amp;query=Fox%2C+J+G">Jason G Fox</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a>, <a href="/search/cs?searchtype=author&amp;query=Mapes%2C+D">Dan Mapes</a>, <a href="/search/cs?searchtype=author&amp;query=Ren%C3%A9%2C+G">Gabriel Ren茅</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2212.01354v2-abstract-short" style="display: inline;"> This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants -- what we call &#39;&#39;shared intelligence&#39;&#39;. This vision is premised on active inference, a formulation of adaptive behavior that can be read&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2212.01354v2-abstract-full').style.display = 'inline'; document.getElementById('2212.01354v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2212.01354v2-abstract-full" style="display: none;"> This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants -- what we call &#39;&#39;shared intelligence&#39;&#39;. This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence, and which inherits from the physics of self-organization. In this context, we understand intelligence as the capacity to accumulate evidence for a generative model of one&#39;s sensed world -- also known as self-evidencing. Formally, this corresponds to maximizing (Bayesian) model evidence, via belief updating over several scales: i.e., inference, learning, and model selection. Operationally, this self-evidencing can be realized via (variational) message passing or belief propagation on a factor graph. Crucially, active inference foregrounds an existential imperative of intelligent systems; namely, curiosity or the resolution of uncertainty. This same imperative underwrites belief sharing in ensembles of agents, in which certain aspects (i.e., factors) of each agent&#39;s generative world model provide a common ground or frame of reference. Active inference plays a foundational role in this ecology of belief sharing -- leading to a formal account of collective intelligence that rests on shared narratives and goals. We also consider the kinds of communication protocols that must be developed to enable such an ecosystem of intelligences and motivate the development of a shared hyper-spatial modeling language and transaction protocol, as a first -- and key -- step towards such an ecology. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2212.01354v2-abstract-full').style.display = 'none'; document.getElementById('2212.01354v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 2 December, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">23+18 pages, one figure, one six page appendix</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Collective Intelligence, 3(1), 2024 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2201.05445">arXiv:2201.05445</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2201.05445">pdf</a>, <a href="https://arxiv.org/format/2201.05445">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Machine Learning of polymer types from the spectral signature of Raman spectroscopy microplastics data </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Ramanna%2C+S">Sheela Ramanna</a>, <a href="/search/cs?searchtype=author&amp;query=Morozovskii%2C+D">Danila Morozovskii</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Sam Swanson</a>, <a href="/search/cs?searchtype=author&amp;query=Bruneau%2C+J">Jennifer Bruneau</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2201.05445v1-abstract-short" style="display: inline;"> The tools and technology that are currently used to analyze chemical compound structures that identify polymer types in microplastics are not well-calibrated for environmentally weathered microplastics. Microplastics that have been degraded by environmental weathering factors can offer less analytic certainty than samples of microplastics that have not been exposed to weathering processes. Machine&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.05445v1-abstract-full').style.display = 'inline'; document.getElementById('2201.05445v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2201.05445v1-abstract-full" style="display: none;"> The tools and technology that are currently used to analyze chemical compound structures that identify polymer types in microplastics are not well-calibrated for environmentally weathered microplastics. Microplastics that have been degraded by environmental weathering factors can offer less analytic certainty than samples of microplastics that have not been exposed to weathering processes. Machine learning tools and techniques allow us to better calibrate the research tools for certainty in microplastics analysis. In this paper, we investigate whether the signatures (Raman shift values) are distinct enough such that well studied machine learning (ML) algorithms can learn to identify polymer types using a relatively small amount of labeled input data when the samples have not been impacted by environmental degradation. Several ML models were trained on a well-known repository, Spectral Libraries of Plastic Particles (SLOPP), that contain Raman shift and intensity results for a range of plastic particles, then tested on environmentally aged plastic particles (SloPP-E) consisting of 22 polymer types. After extensive preprocessing and augmentation, the trained random forest model was then tested on the SloPP-E dataset resulting in an improvement in classification accuracy of 93.81% from 89%. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2201.05445v1-abstract-full').style.display = 'none'; document.getElementById('2201.05445v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 14 January, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1908.03583">arXiv:1908.03583</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1908.03583">pdf</a>, <a href="https://arxiv.org/format/1908.03583">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Performance">cs.PF</span> </div> </div> <p class="title is-5 mathjax"> An Empirical Guide to the Behavior and Use of Scalable Persistent Memory </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Yang%2C+J">Jian Yang</a>, <a href="/search/cs?searchtype=author&amp;query=Kim%2C+J">Juno Kim</a>, <a href="/search/cs?searchtype=author&amp;query=Hoseinzadeh%2C+M">Morteza Hoseinzadeh</a>, <a href="/search/cs?searchtype=author&amp;query=Izraelevitz%2C+J">Joseph Izraelevitz</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1908.03583v1-abstract-short" style="display: inline;"> After nearly a decade of anticipation, scalable nonvolatile memory DIMMs are finally commercially available with the release of Intel&#39;s 3D XPoint DIMM. This new nonvolatile DIMM supports byte-granularity accesses with access times on the order of DRAM, while also providing data storage that survives power outages. Researchers have not idly waited for real nonvolatile DIMMs (NVDIMMs) to arrive. Ove&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1908.03583v1-abstract-full').style.display = 'inline'; document.getElementById('1908.03583v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1908.03583v1-abstract-full" style="display: none;"> After nearly a decade of anticipation, scalable nonvolatile memory DIMMs are finally commercially available with the release of Intel&#39;s 3D XPoint DIMM. This new nonvolatile DIMM supports byte-granularity accesses with access times on the order of DRAM, while also providing data storage that survives power outages. Researchers have not idly waited for real nonvolatile DIMMs (NVDIMMs) to arrive. Over the past decade, they have written a slew of papers proposing new programming models, file systems, libraries, and applications built to exploit the performance and flexibility that NVDIMMs promised to deliver. Those papers drew conclusions and made design decisions without detailed knowledge of how real NVDIMMs would behave or how industry would integrate them into computer architectures. Now that 3D XPoint NVDIMMs are actually here, we can provide detailed performance numbers, concrete guidance for programmers on these systems, reevaluate prior art for performance, and reoptimize persistent memory software for the real 3D XPoint DIMM. In this paper, we explore the performance properties and characteristics of Intel&#39;s new 3D XPoint DIMM at the micro and macro level. First, we investigate the basic characteristics of the device, taking special note of the particular ways in which its performance is peculiar relative to traditional DRAM or other past methods used to emulate NVM. From these observations, we recommend a set of best practices to maximize the performance of the device. With our improved understanding, we then explore the performance of prior art in application-level software for persistent memory, taking note of where their performance was influenced by our guidelines. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1908.03583v1-abstract-full').style.display = 'none'; document.getElementById('1908.03583v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 August, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2019. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1904.10083">arXiv:1904.10083</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1904.10083">pdf</a>, <a href="https://arxiv.org/format/1904.10083">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> </div> </div> <p class="title is-5 mathjax"> Pangolin: A Fault-Tolerant Persistent Memory Programming Library </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Zhang%2C+L">Lu Zhang</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1904.10083v2-abstract-short" style="display: inline;"> Non-volatile main memory (NVMM) allows programmers to build complex, persistent, pointer-based data structures that can offer substantial performance gains over conventional approaches to managing persistent state. This programming model removes the file system from the critical path which improves performance, but it also places these data structures out of reach of file system-based fault tolera&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1904.10083v2-abstract-full').style.display = 'inline'; document.getElementById('1904.10083v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1904.10083v2-abstract-full" style="display: none;"> Non-volatile main memory (NVMM) allows programmers to build complex, persistent, pointer-based data structures that can offer substantial performance gains over conventional approaches to managing persistent state. This programming model removes the file system from the critical path which improves performance, but it also places these data structures out of reach of file system-based fault tolerance mechanisms (e.g., block-based checksums or erasure coding). Without fault-tolerance, using NVMM to hold critical data will be much less attractive. This paper presents Pangolin, a fault-tolerant persistent object library designed for NVMM. Pangolin uses a combination of checksums, parity, and micro-buffering to protect an application&#39;s objects from both media errors and corruption due to software bugs. It provides these protections for objects of any size and supports automatic, online detection of data corruption and recovery. The required storage overhead is small (1% for gigabyte-sized pools of NVMM). Pangolin provides stronger protection, requires orders of magnitude less storage overhead, and achieves comparable performance relative to the current state-of-the-art fault-tolerant persistent object library. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1904.10083v2-abstract-full').style.display = 'none'; document.getElementById('1904.10083v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 July, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 22 April, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2019. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1903.05714">arXiv:1903.05714</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1903.05714">pdf</a>, <a href="https://arxiv.org/format/1903.05714">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Performance">cs.PF</span> </div> </div> <p class="title is-5 mathjax"> Basic Performance Measurements of the Intel Optane DC Persistent Memory Module </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Izraelevitz%2C+J">Joseph Izraelevitz</a>, <a href="/search/cs?searchtype=author&amp;query=Yang%2C+J">Jian Yang</a>, <a href="/search/cs?searchtype=author&amp;query=Zhang%2C+L">Lu Zhang</a>, <a href="/search/cs?searchtype=author&amp;query=Kim%2C+J">Juno Kim</a>, <a href="/search/cs?searchtype=author&amp;query=Liu%2C+X">Xiao Liu</a>, <a href="/search/cs?searchtype=author&amp;query=Memaripour%2C+A">Amirsaman Memaripour</a>, <a href="/search/cs?searchtype=author&amp;query=Soh%2C+Y+J">Yun Joon Soh</a>, <a href="/search/cs?searchtype=author&amp;query=Wang%2C+Z">Zixuan Wang</a>, <a href="/search/cs?searchtype=author&amp;query=Xu%2C+Y">Yi Xu</a>, <a href="/search/cs?searchtype=author&amp;query=Dulloor%2C+S+R">Subramanya R. Dulloor</a>, <a href="/search/cs?searchtype=author&amp;query=Zhao%2C+J">Jishen Zhao</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1903.05714v3-abstract-short" style="display: inline;"> Scalable nonvolatile memory DIMMs will finally be commercially available with the release of the Intel Optane DC Persistent Memory Module (or just &#34;Optane DC PMM&#34;). This new nonvolatile DIMM supports byte-granularity accesses with access times on the order of DRAM, while also providing data storage that survives power outages. This work comprises the first in-depth, scholarly, performance review o&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1903.05714v3-abstract-full').style.display = 'inline'; document.getElementById('1903.05714v3-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1903.05714v3-abstract-full" style="display: none;"> Scalable nonvolatile memory DIMMs will finally be commercially available with the release of the Intel Optane DC Persistent Memory Module (or just &#34;Optane DC PMM&#34;). This new nonvolatile DIMM supports byte-granularity accesses with access times on the order of DRAM, while also providing data storage that survives power outages. This work comprises the first in-depth, scholarly, performance review of Intel&#39;s Optane DC PMM, exploring its capabilities as a main memory device, and as persistent, byte-addressable memory exposed to user-space applications. This report details the technologies performance under a number of modes and scenarios, and across a wide variety of macro-scale benchmarks. Optane DC PMMs can be used as large memory devices with a DRAM cache to hide their lower bandwidth and higher latency. When used in this Memory (or cached) mode, Optane DC memory has little impact on applications with small memory footprints. Applications with larger memory footprints may experience some slow-down relative to DRAM, but are now able to keep much more data in memory. When used under a file system, Optane DC PMMs can result in significant performance gains, especially when the file system is optimized to use the load/store interface of the Optane DC PMM and the application uses many small, persistent writes. For instance, using the NOVA-relaxed NVMM file system, we can improve the performance of Kyoto Cabinet by almost 2x. Optane DC PMMs can also enable user-space persistence where the application explicitly controls its writes into persistent Optane DC media. In our experiments, modified applications that used user-space Optane DC persistence generally outperformed their file system counterparts. For instance, the persistent version of RocksDB performed almost 2x faster than the equivalent program utilizing an NVMM-aware file system. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1903.05714v3-abstract-full').style.display = 'none'; document.getElementById('1903.05714v3-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 August, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 13 March, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2019. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1810.07646">arXiv:1810.07646</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1810.07646">pdf</a>, <a href="https://arxiv.org/format/1810.07646">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> </div> </div> <p class="title is-5 mathjax"> Trial by Flyer: Building Quadcopters From Scratch in a Ten-Week Capstone Course </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1810.07646v3-abstract-short" style="display: inline;"> We describe our experience teaching an intensive capstone course in which pairs of students build the hardware and software for a remote-controller quad-rotor aircraft (i.e., a quadcopter or &#34;drone&#34;) from scratch in one 10-week quarter. The course covers printed circuit board (PCB) design and assembly, basic control theory and sensor fusion, and embedded systems programming. To reduce the workload&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1810.07646v3-abstract-full').style.display = 'inline'; document.getElementById('1810.07646v3-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1810.07646v3-abstract-full" style="display: none;"> We describe our experience teaching an intensive capstone course in which pairs of students build the hardware and software for a remote-controller quad-rotor aircraft (i.e., a quadcopter or &#34;drone&#34;) from scratch in one 10-week quarter. The course covers printed circuit board (PCB) design and assembly, basic control theory and sensor fusion, and embedded systems programming. To reduce the workload on course staff and provide higher-quality feedback on student designs, we have implemented an automated PCB design checking tool/autograder. We describe the course content in detail, identify the challenges it presents to students and course staff, and propose changes to further increase student success and improve the scalability of the course. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1810.07646v3-abstract-full').style.display = 'none'; document.getElementById('1810.07646v3-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 27 February, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 1 October, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2018. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1805.01988">arXiv:1805.01988</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1805.01988">pdf</a>, <a href="https://arxiv.org/format/1805.01988">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Performance">cs.PF</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/PCCC.2017.8280433">10.1109/PCCC.2017.8280433 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> AutoTiering: Automatic Data Placement Manager in Multi-Tier All-Flash Datacenter </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Yang%2C+Z">Zhengyu Yang</a>, <a href="/search/cs?searchtype=author&amp;query=Hoseinzadeh%2C+M">Morteza Hoseinzadeh</a>, <a href="/search/cs?searchtype=author&amp;query=Andrews%2C+A">Allen Andrews</a>, <a href="/search/cs?searchtype=author&amp;query=Mayers%2C+C">Clay Mayers</a>, <a href="/search/cs?searchtype=author&amp;query=Evans%2C+D">David Evans</a>, <a href="/search/cs?searchtype=author&amp;query=Bolt%2C+R">Rory Bolt</a>, <a href="/search/cs?searchtype=author&amp;query=Bhimani%2C+J">Janki Bhimani</a>, <a href="/search/cs?searchtype=author&amp;query=Mi%2C+N">Ningfang Mi</a>, <a href="/search/cs?searchtype=author&amp;query=Swanson%2C+S">Steven Swanson</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1805.01988v1-abstract-short" style="display: inline;"> In the year of 2017, the capital expenditure of Flash-based Solid State Drivers (SSDs) keeps declining and the storage capacity of SSDs keeps increasing. As a result, the &#34;selling point&#34; of traditional spinning Hard Disk Drives (HDDs) as a backend storage - low cost and large capacity - is no longer unique, and eventually they will be replaced by low-end SSDs which have large capacity but perform&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1805.01988v1-abstract-full').style.display = 'inline'; document.getElementById('1805.01988v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1805.01988v1-abstract-full" style="display: none;"> In the year of 2017, the capital expenditure of Flash-based Solid State Drivers (SSDs) keeps declining and the storage capacity of SSDs keeps increasing. As a result, the &#34;selling point&#34; of traditional spinning Hard Disk Drives (HDDs) as a backend storage - low cost and large capacity - is no longer unique, and eventually they will be replaced by low-end SSDs which have large capacity but perform orders of magnitude better than HDDs. Thus, it is widely believed that all-flash multi-tier storage systems will be adopted in the enterprise datacenters in the near future. However, existing caching or tiering solutions for SSD-HDD hybrid storage systems are not suitable for all-flash storage systems. This is because that all-flash storage systems do not have a large speed difference (e.g., 10x) among each tier. Instead, different specialties (such as high performance, high capacity, etc.) of each tier should be taken into consideration. Motivated by this, we develop an automatic data placement manager called &#34;AutoTiering&#34; to handle virtual machine disk files (VMDK) allocation and migration in an all-flash multi-tier datacenter to best utilize the storage resource, optimize the performance, and reduce the migration overhead. AutoTiering is based on an optimization framework, whose core technique is to predict VM&#39;s performance change on different tiers with different specialties without conducting real migration. As far as we know, AutoTiering is the first optimization solution designed for all-flash multi-tier datacenters. We implement AutoTiering on VMware ESXi, and experimental results show that it can significantly improve the I/O performance compared to existing solutions. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1805.01988v1-abstract-full').style.display = 'none'; document.getElementById('1805.01988v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 May, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2018. </p> </li> </ol> <div class="is-hidden-tablet"> <!-- feedback for mobile only --> <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>&nbsp;&nbsp;</span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary"> <!-- MetaColumn 1 --> <div 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