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Distributed algorithms that operate in the fail-recovery model rely on the state stored in stable memory to guarantee the irreversibility of operations even in the presence of failures. The performance of these algorithms lean heavily on…

Operating Systems · Computer Science 2020-02-19 William B. Mingardi , Gustavo M. D. Vieira

Persistent Memory (PM) is non-volatile byte-addressable memory that offers read and write latencies in the order of magnitude smaller than flash storage, such as SSDs. This survey discusses how file systems address the most prominent…

Operating Systems · Computer Science 2023-10-05 Wiebe van Breukelen , Animesh Trivedi

Conventional computing paradigm struggles to fulfill the rapidly growing demands from emerging applications, especially those for machine intelligence, because much of the power and energy is consumed by constant data transfers between…

Development of memory devices with ultimate performance has played a key role in innovation of modern electronics. As a mainstream technology nonvolatile memory devices have manifested high capacity and mechanical reliability, however…

State-of-the-art \emph{software transactional memory (STM)} implementations achieve good performance by carefully avoiding the overhead of \emph{incremental validation} (i.e., re-reading previously read data items to avoid inconsistency)…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-08 Trevor Brown , Srivatsan Ravi

The recent availability of fast, dense, byte-addressable non-volatile memory has led to increasing interest in the problem of designing and specifying durable data structures that can recover from system crashes. However, designing durable…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-29 Michal Friedman , Naama Ben-David , Yuanhao Wei , Guy E. Blelloch , Erez Petrank

Balancing sensitivity to new tasks and stability for retaining past knowledge is crucial in continual learning (CL). Recently, sharpness-aware minimization has proven effective in transfer learning and has also been adopted in continual…

Machine Learning · Computer Science 2025-09-01 Wei Li , Hangjie Yuan , Zixiang Zhao , Yifan Zhu , Aojun Lu , Tao Feng , Yanan Sun

Emerging Non-Volatile Memories (NVMs) are promising contenders for building future memory systems. On the other side, unlike DRAM systems, NVMs can retain data even after power loss and thus enlarge the attack surface. While data encryption…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-24 Amro Awad , Laurent Njilla , Mao Ye

Persistent memory (PM) is an emerging class of storage technology that combines the benefits of DRAM and SSD. This characteristic inspires research on persistent objects in PM with fine-grained concurrency control. Among such objects,…

Programming Languages · Computer Science 2022-03-16 Kyeongmin Cho , Seungmin Jeon , Jeehoon Kang

Neural Turing Machines (NTM) contain memory component that simulates "working memory" in the brain to store and retrieve information to ease simple algorithms learning. So far, only linearly organized memory is proposed, and during…

Artificial Intelligence · Computer Science 2015-10-27 Wei Zhang , Yang Yu , Bowen Zhou

Many high end and next generation computing systems to incorporated alternative memory technologies to meet performance goals. Since these technologies present distinct advantages and tradeoffs compared to conventional DDR* SDRAM, such as…

Performance · Computer Science 2021-10-06 M. Ben Olson , Brandon Kammerdiener , Kshitij A. Doshi , Terry Jones , Michael R. Jantz

Programming with replicated objects is difficult. Developers must face the fundamental trade-off between consistency and performance head on, while struggling with the complexity of distributed storage stacks. We introduce Correctables, a…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-09-09 Rachid Guerraoui , Matej Pavlovic , Dragos-Adrian Seredinschi

Training deep neural network classifiers that are certifiably robust against adversarial attacks is critical to ensuring the security and reliability of AI-controlled systems. Although numerous state-of-the-art certified training methods…

Machine Learning · Computer Science 2022-10-27 Pratik Vaishnavi , Kevin Eykholt , Amir Rahmati

Transformer models rely on High-Performance Computing (HPC) resources for inference, where soft errors are inevitable in large-scale systems, making the reliability of the model particularly critical. Existing fault tolerance frameworks for…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-14 Huangliang Dai , Shixun Wu , Jiajun Huang , Zizhe Jian , Yue Zhu , Haiyang Hu , Zizhong Chen

Click-through rate (CTR) prediction is of great importance in recommendation systems and online advertising platforms. When served in industrial scenarios, the user-generated data observed by the CTR model typically arrives as a stream.…

Information Retrieval · Computer Science 2023-04-19 Congcong Liu , Fei Teng , Xiwei Zhao , Zhangang Lin , Jinghe Hu , Jingping Shao

Persistent Memory (PM) makes possible recoverable applications that can preserve application progress across system reboots and power failures. Actual recoverability requires careful ordering of cacheline flushes, currently done in two…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-02 Swapnil Haria , Mark D. Hill , Michael M. Swift

Scalable persistent memory (PM) has opened up new opportunities for building indexes that operate and persist data directly on the memory bus, potentially enabling instant recovery, low latency and high throughput. When real PM hardware…

Databases · Computer Science 2022-07-29 Yuliang He , Duo Lu , Kaisong Huang , Tianzheng Wang

Oblivious RAM (ORAM) is a provable secure primitive to prevent access pattern leakage on the memory bus. It serves as the intermediate layer between the trusted on-chip components and the untrusted external memory systems to modulate the…

Hardware Architecture · Computer Science 2023-01-03 Gang Liu , Kenli Li , Zheng Xiao , Rujia Wang

Synchronous Mirroring (SM) is a standard approach to building highly-available and fault-tolerant enterprise storage systems. SM ensures strong data consistency by maintaining multiple exact data replicas and synchronously propagating every…

Over the past few decades, the hydrology community has witnessed notable advancements in streamflow prediction, particularly with the introduction of cutting-edge machine-learning algorithms. Recurrent neural networks, especially Long…

Machine Learning · Computer Science 2023-05-23 Sinan Rasiya Koya , Tirthankar Roy