Log in

Relevant bibliographies by topics / Disaggregated Memory / Journal articles

To see the other types of publications on this topic, follow the link: Disaggregated Memory.

Journal articles on the topic 'Disaggregated Memory'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Disaggregated Memory.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Calciu, Irina, M. Talha Imran, Ivan Puddu, et al. "Using Local Cache Coherence for Disaggregated Memory Systems." ACM SIGOPS Operating Systems Review 57, no. 1 (2023): 21–28. http://dx.doi.org/10.1145/3606557.3606561.

Full text

Abstract:

Disaggregated memory provides many cost savings and resource provisioning benefits for current datacenters, but software systems enabling disaggregated memory access result in high performance penalties. These systems require intrusive code changes to port applications for disaggregated memory or employ slow virtual memory mechanisms to avoid code changes. Such mechanisms result in high overhead page faults to access remote data and high dirty data amplification when tracking changes to cached data at page-granularity. In this paper, we propose a fundamentally new approach for disaggregated me

APA, Harvard, Vancouver, ISO, and other styles

2

Cao, Wenqi, and Ling Liu. "Hierarchical Orchestration of Disaggregated Memory." IEEE Transactions on Computers 69, no. 6 (2020): 844–55. http://dx.doi.org/10.1109/tc.2020.2968525.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Min, Xinhao, Kai Lu, Pengyu Liu, et al. "SepHash: A Write-Optimized Hash Index On Disaggregated Memory via Separate Segment Structure." Proceedings of the VLDB Endowment 17, no. 5 (2024): 1091–104. http://dx.doi.org/10.14778/3641204.3641218.

Full text

Abstract:

Disaggregated memory separates compute and memory resources into independent pools connected by fast RDMA (Remote Direct Memory Access) networks, which can improve memory utilization, reduce cost, and enable elastic scaling of compute and memory resources. Hash indexes provide high-performance single-point operations and are widely used in distributed systems and databases. However, under disaggregated memory, existing hash indexes suffer from write performance degradation due to high resize overhead and concurrency control overhead. Traditional write-optimized hash indexes are not efficient f

APA, Harvard, Vancouver, ISO, and other styles

4

Maruf, Hasan Al, Yuhong Zhong, Hongyi Wang, Mosharaf Chowdhury, Asaf Cidon, and Carl Waldspurger. "Memtrade: Marketplace for Disaggregated Memory Clouds." ACM SIGMETRICS Performance Evaluation Review 51, no. 1 (2023): 1–2. http://dx.doi.org/10.1145/3606376.3593553.

Full text

Abstract:

We present Memtrade, the first practical marketplace for disaggregated memory clouds. Clouds introduce a set of unique challenges for resource disaggregation across different tenants, including resource harvesting, isolation, and matching. Memtrade allows producer virtual machines (VMs) to lease both their unallocated memory and allocated-but-idle application memory to remote consumer VMs for a limited period of time. Memtrade does not require any modifications to host-level system software or support from the cloud provider. It harvests producer memory using an application-aware control loop

APA, Harvard, Vancouver, ISO, and other styles

5

Maruf, Hasan Al, Yuhong Zhong, Hongyi Wang, Mosharaf Chowdhury, Asaf Cidon, and Carl Waldspurger. "Memtrade: Marketplace for Disaggregated Memory Clouds." Proceedings of the ACM on Measurement and Analysis of Computing Systems 7, no. 2 (2023): 1–27. http://dx.doi.org/10.1145/3589985.

Full text

Abstract:

We present Memtrade, the first practical marketplace for disaggregated memory clouds. Clouds introduce a set of unique challenges for resource disaggregation across different tenants, including resource harvesting, isolation, and matching. Memtrade allows producer virtual machines (VMs) to lease both their unallocated memory and allocated-but-idle application memory to remote consumer VMs for a limited period of time. Memtrade does not require any modifications to host-level system software or support from the cloud provider. It harvests producer memory using an application-aware control loop

APA, Harvard, Vancouver, ISO, and other styles

6

Koo, Bonmoo, Jaesang Hwang, Jonghyeok Park, and Wook-Hee Kim. "Converting Concurrent Range Index Structure to Range Index Structure for Disaggregated Memory." Applied Sciences 13, no. 20 (2023): 11130. http://dx.doi.org/10.3390/app132011130.

Full text

Abstract:

In this work, we propose the Spread approach, which tailors a concurrent range index structure to a range index structure for disaggregated memory connected via RDMA (Remote Direct Memory Access). The Spread approach leverages the concept of tolerating transient inconsistencies in a concurrent range index structure to reduce the amount of expensive RDMA operations. Based on the Spread approach, we converted Blink-tree, a concurrent range index structure, to a range index structure for disaggregated memory called RF-tree. In our experimental study, RF-tree shows comparable performance to Sherma

APA, Harvard, Vancouver, ISO, and other styles

7

Ishizaki, Teruaki, and Yoshiro Yamabe. "Memory-centric Architecture for Disaggregated Computers." NTT Technical Review 19, no. 7 (2021): 65–69. http://dx.doi.org/10.53829/ntr202107fa9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Alachiotis, Nikolaos, Panagiotis Skrimponis, Manolis Pissadakis, and Dionisios Pnevmatikatos. "Scalable Phylogeny Reconstruction with Disaggregated Near-memory Processing." ACM Transactions on Reconfigurable Technology and Systems 15, no. 3 (2022): 1–32. http://dx.doi.org/10.1145/3484983.

Full text

Abstract:

Disaggregated computer architectures eliminate resource fragmentation in next-generation datacenters by enabling virtual machines to employ resources such as CPUs, memory, and accelerators that are physically located on different servers. While this paves the way for highly compute- and/or memory-intensive applications to potentially deploy all CPUs and/or memory resources in a datacenter, it poses a major challenge to the efficient deployment of hardware accelerators: input/output data can reside on different servers than the ones hosting accelerator resources, thereby requiring time- and ene

APA, Harvard, Vancouver, ISO, and other styles

9

Widmoser, Manuel, Daniel Kocher, and Nikolaus Augsten. "Scalable Distributed Inverted List Indexes in Disaggregated Memory." Proceedings of the ACM on Management of Data 2, no. 3 (2024): 1–27. http://dx.doi.org/10.1145/3654974.

Full text

Abstract:

Memory disaggregation separates compute (CPU) and main memory resources into disjoint physical units to enable elastic and independent scaling. Connected via high-speed RDMA-enabled networks, compute nodes can directly access remote memory. This setting often requires complex protocols with many network roundtrips as memory nodes have near-zero compute power. In this paper, we design a scalable distributed inverted list index for disaggregated memory architectures. An inverted list index maps a set of terms to lists of documents that contain this term. Current solutions either partition the in

APA, Harvard, Vancouver, ISO, and other styles

10

Lu, Baotong, Kaisong Huang, Chieh-Jan Mike Liang, Tianzheng Wang, and Eric Lo. "DEX: Scalable Range Indexing on Disaggregated Memory." Proceedings of the VLDB Endowment 17, no. 10 (2024): 2603–16. http://dx.doi.org/10.14778/3675034.3675050.

Full text

Abstract:

Memory disaggregation can potentially allow memory-optimized range indexes such as B+-trees to scale beyond one machine while attaining high hardware utilization and low cost. Designing scalable indexes on disaggregated memory, however, is challenging due to rudimentary caching, unprincipled offloading and excessive inconsistency among servers. This paper proposes DEX, a new scalable B+-tree for memory disaggregation. DEX includes a set of techniques to reduce remote accesses, including logical partitioning, lightweight caching and cost-aware offloading. Our evaluation shows that DEX can outpe

APA, Harvard, Vancouver, ISO, and other styles

11

Wang, Qing, Youyou Lu, and Jiwu Shu. "Building Write-Optimized Tree Indexes on Disaggregated Memory." ACM SIGMOD Record 52, no. 1 (2023): 45–52. http://dx.doi.org/10.1145/3604437.3604448.

Full text

Abstract:

Memory disaggregation architecture physically separates CPU and memory into independent components, which are connected via high-speed RDMA networks, greatly improving resource utilization of database systems. However, such an architecture poses unique challenges to data indexing due to limited RDMA semantics and near-zero computation power at memory side. Existing indexes supporting disaggregated memory either suffer from low write performance, or require hardware modification.

APA, Harvard, Vancouver, ISO, and other styles

12

Jeong, Yeonwoo, Gyeonghwan Jung, Kyuli Park, Youngjae Kim, and Sungyong Park. "Empirical Analysis of Disaggregated Cloud Memory on Memory Intensive Applications." JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE 23, no. 5 (2023): 273–82. http://dx.doi.org/10.5573/jsts.2023.23.5.273.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Gonzalez, Jorge, Mauricio G. Palma, Maarten Hattink, et al. "Optically connected memory for disaggregated data centers." Journal of Parallel and Distributed Computing 163 (May 2022): 300–312. http://dx.doi.org/10.1016/j.jpdc.2022.01.013.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Koh, Kwangwon, Kangho Kim, Seunghyub Jeon, and Jaehyuk Huh. "Disaggregated Cloud Memory with Elastic Block Management." IEEE Transactions on Computers 68, no. 1 (2019): 39–52. http://dx.doi.org/10.1109/tc.2018.2851565.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Kwon, Youngeun, and Minsoo Rhu. "A Disaggregated Memory System for Deep Learning." IEEE Micro 39, no. 5 (2019): 82–90. http://dx.doi.org/10.1109/mm.2019.2929165.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Ewais, Mohammad, and Paul Chow. "Disaggregated Memory in the Datacenter: A Survey." IEEE Access 11 (2023): 20688–712. http://dx.doi.org/10.1109/access.2023.3250407.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Liu, Yi, Minghao Xie, Shouqian Shi, Yuanchao Xu, Heiner Litz, and Chen Qian. "Outback: Fast and Communication-Efficient Index for Key-Value Store on Disaggregated Memory." Proceedings of the VLDB Endowment 18, no. 2 (2024): 335–48. https://doi.org/10.14778/3705829.3705849.

Full text

Abstract:

Disaggregated memory systems achieve resource utilization efficiency and system scalability by distributing computation and memory resources into distinct pools of nodes. RDMA is an attractive solution to support high-throughput communication between different disaggregated resource pools. However, existing RDMA solutions face a dilemma: one-sided RDMA completely bypasses computation at memory nodes, but its communication takes multiple round trips; two-sided RDMA achieves one-round-trip communication but requires non-trivial computation for index lookups at memory nodes, which violates the pr

APA, Harvard, Vancouver, ISO, and other styles

18

Giannoula, Christina, Kailong Huang, Jonathan Tang, et al. "Architectural Support for Efficient Data Movement in Fully Disaggregated Systems." ACM SIGMETRICS Performance Evaluation Review 51, no. 1 (2023): 5–6. http://dx.doi.org/10.1145/3606376.3593533.

Full text

Abstract:

Traditional data centers include monolithic servers that tightly integrate CPU, memory and disk (Figure 1a). Instead, Disaggregated Systems (DSs) [8, 13, 18, 27] organize multiple compute (CC), memory (MC) and storage devices as independent, failure-isolated components interconnected over a high-bandwidth network (Figure 1b). DSs can greatly reduce data center costs by providing improved resource utilization, resource scaling, failure-handling and elasticity in modern data centers [5, 8-10, 10, 11, 13, 18, 27] The MCs provide large pools of main memory (remote memory), while the CCs include th

APA, Harvard, Vancouver, ISO, and other styles

19

Lim, Kevin, Jichuan Chang, Trevor Mudge, Parthasarathy Ranganathan, Steven K. Reinhardt, and Thomas F. Wenisch. "Disaggregated memory for expansion and sharing in blade servers." ACM SIGARCH Computer Architecture News 37, no. 3 (2009): 267–78. http://dx.doi.org/10.1145/1555815.1555789.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Lu, Mengting, Gaocong Liu, Kun Wang, Feng Zhu, and Shu Li. "CHash: A High Cost-Performance Hash Design for CXL-based Disaggregated Memory System." ACM SIGMETRICS Performance Evaluation Review 53, no. 1 (2025): 124–26. https://doi.org/10.1145/3744970.3727278.

Full text

Abstract:

The exponential growth in demand for high-performance computing systems has created an urgent requirement for innovative memory technologies that can provide higher bandwidth and enhanced capacity scalability. In particular, Compute Express Link (CXL) has emerged as a promising solution for memory expansion and system acceleration. Hash-based index structures are widely recognized as fundamental components of in-memory database systems, and they are commonly used for indexing in-memory key-value stores due to their capability for rapid lookup performance. How to design and maintain a hash inde

APA, Harvard, Vancouver, ISO, and other styles

21

Lu, Mengting, Gaocong Liu, Kun Wang, Feng Zhu, and Shu Li. "CHash: A High Cost-Performance Hash Design for CXL-based Disaggregated Memory System." Proceedings of the ACM on Measurement and Analysis of Computing Systems 9, no. 1 (2025): 1–22. https://doi.org/10.1145/3711698.

Full text

Abstract:

The exponential growth in demand for high-performance computing systems has created an urgent requirement for innovative memory technologies that can provide higher bandwidth and enhanced capacity scalability. In particular, Compute Express Link (CXL) has emerged as a promising solution for memory expansion and system acceleration. Hash-based index structures are widely recognized as fundamental components of in-memory database systems, and they are commonly used for indexing in-memory key-value stores due to their capability for rapid lookup performance. How to design and maintain a hash inde

APA, Harvard, Vancouver, ISO, and other styles

22

Miller, Ethan, Achilles Benetopoulos, George Neville-Neil, Pankaj Mehra, and Daniel Bittman. "Pointers in Far Memory." Queue 21, no. 3 (2023): 75–93. http://dx.doi.org/10.1145/3606029.

Full text

Abstract:

Effectively exploiting emerging far-memory technology requires consideration of operating on richly connected data outside the context of the parent process. Operating-system technology in development offers help by exposing abstractions such as memory objects and globally invariant pointers that can be traversed by devices and newly instantiated compute. Such ideas will allow applications running on future heterogeneous distributed systems with disaggregated memory nodes to exploit near-memory processing for higher performance and to independently scale their memory and compute resources for

APA, Harvard, Vancouver, ISO, and other styles

23

Yong, Yewon, Taehoon Kim, Sungho Lee, and Changdae Kim. "A Software-based Secure Disaggregated Memory System on Commodity Servers." Journal of KIISE 51, no. 9 (2024): 757–70. http://dx.doi.org/10.5626/jok.2024.51.9.757.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Barros, Carlos Pestana, Luis A. Gil-Alana, and James E. Payne. "U.S. Disaggregated renewable energy consumption: Persistence and long memory behavior." Energy Economics 40 (November 2013): 425–32. http://dx.doi.org/10.1016/j.eneco.2013.07.018.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Giannoula, Christina, Kailong Huang, Jonathan Tang, et al. "DaeMon: Architectural Support for Efficient Data Movement in Fully Disaggregated Systems." Proceedings of the ACM on Measurement and Analysis of Computing Systems 7, no. 1 (2023): 1–36. http://dx.doi.org/10.1145/3579445.

Full text

Abstract:

Resource disaggregation offers a cost effective solution to resource scaling, utilization, and failure-handling in data centers by physically separating hardware devices in a server. Servers are architected as pools of processor, memory, and storage devices, organized as independent failure-isolated components interconnected by a high-bandwidth network. A critical challenge, however, is the high performance penalty of accessing data from a remote memory module over the network. Addressing this challenge is difficult as disaggregated systems have high runtime variability in network latencies/ba

APA, Harvard, Vancouver, ISO, and other styles

26

Matsui, Chihiro, and Ken Takeuchi. "Dynamic Adjustment of Storage Class Memory Capacity in Memory-Resource Disaggregated Hybrid Storage With SCM and NAND Flash Memory." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 27, no. 8 (2019): 1799–810. http://dx.doi.org/10.1109/tvlsi.2019.2905852.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Zou, Mingzhe, Shuyang Zhu, Jiacheng Gu, Lidija M. Korunovic, and Sasa Z. Djokic. "Heating and Lighting Load Disaggregation Using Frequency Components and Convolutional Bidirectional Long Short-Term Memory Method." Energies 14, no. 16 (2021): 4831. http://dx.doi.org/10.3390/en14164831.

Full text

Abstract:

Load disaggregation for the identification of specific load types in the total demands (e.g., demand-manageable loads, such as heating or cooling loads) is becoming increasingly important for the operation of existing and future power supply systems. This paper introduces an approach in which periodical changes in the total demands (e.g., daily, weekly, and seasonal variations) are disaggregated into corresponding frequency components and correlated with the same frequency components in the meteorological variables (e.g., temperature and solar irradiance), allowing to select combinations of fr

APA, Harvard, Vancouver, ISO, and other styles

28

Lee, Sekwon, Soujanya Ponnapalli, Sharad Singhal, Marcos K. Aguilera, Kimberly Keeton, and Vijay Chidambaram. "DINOMO." Proceedings of the VLDB Endowment 15, no. 13 (2022): 4023–37. http://dx.doi.org/10.14778/3565838.3565854.

Full text

Abstract:

We present Dinomo, a novel key-value store for disaggregated persistent memory (DPM). Dinomo is the first key-value store for DPM that simultaneously achieves high common-case performance, scalability, and lightweight online reconfiguration. We observe that previously proposed key-value stores for DPM had architectural limitations that prevent them from achieving all three goals simultaneously. Dinomo uses a novel combination of techniques such as ownership partitioning, disaggregated adaptive caching, selective replication, and lock-free and log-free indexing to achieve these goals. Compared

APA, Harvard, Vancouver, ISO, and other styles

29

Aguilera, Marcos K., Emmanuel Amaro, Nadav Amit, Erika Hunhoff, Anil Yelam, and Gerd Zellweger. "Memory disaggregation: why now and what are the challenges." ACM SIGOPS Operating Systems Review 57, no. 1 (2023): 38–46. http://dx.doi.org/10.1145/3606557.3606563.

Full text

Abstract:

Hardware disaggregation has emerged as one of the most fundamental shifts in how we build computer systems over the past decades. While disaggregation has been successful for several types of resources (storage, power, and others), memory disaggregation has yet to happen. We make the case that the time for memory disaggregation has arrived. We look at past successful disaggregation stories and learn that their success depended on two requirements: addressing a burning issue and being technically feasible. We examine memory disaggregation through this lens and find that both requirements are fi

APA, Harvard, Vancouver, ISO, and other styles

30

Al Maruf, Hasan, and Mosharaf Chowdhury. "Memory Disaggregation: Advances and Open Challenges." ACM SIGOPS Operating Systems Review 57, no. 1 (2023): 29–37. http://dx.doi.org/10.1145/3606557.3606562.

Full text

Abstract:

Compute and memory are tightly coupled within each server in traditional datacenters. Large-scale datacenter operators have identified this coupling as a root cause behind fleetwide resource underutilization and increasing Total Cost of Ownership (TCO). With the advent of ultra-fast networks and cache-coherent interfaces, memory disaggregation has emerged as a potential solution, whereby applications can leverage available memory even outside server boundaries. This paper summarizes the growing research landscape of memory disaggregation from a software perspective and introduces the challenge

APA, Harvard, Vancouver, ISO, and other styles

31

McFall, G. Peggy, Lars Bäckman, and Roger A. Dixon. "Nuances in Alzheimer’s Genetic Risk Reveal Differential Predictions of Non-demented Memory Aging Trajectories: Selective Patterns by APOE Genotype and Sex." Current Alzheimer Research 16, no. 4 (2019): 302–15. http://dx.doi.org/10.2174/1567205016666190315094452.

Full text

Abstract:

Background: Apolipoprotein E (APOE) is a prominent genetic risk factor for Alzheimer’s disease (AD) and a frequent target for associations with non-demented and cognitively impaired aging. APOE offers a unique opportunity to evaluate two dichotomous comparisons and selected gradations of APOE risk. Some evidence suggests that APOE effects may differ by sex and emerge especially in interaction with other AD-related biomarkers (e.g., vascular health). Methods: Longitudinal trajectories of non-demented adults (n = 632, 67% female, Mage = 68.9) populated a 40-year band of aging. Focusing on memory

APA, Harvard, Vancouver, ISO, and other styles

32

Phani Suresh Paladugu. "Hierarchical Memory Systems for AI Workloads: From Architecture to Optimization." Journal of Computer Science and Technology Studies 7, no. 7 (2025): 971–78. https://doi.org/10.32996/jcsts.2025.7.7.107.

Full text

Abstract:

Memory architecture has transformed from a secondary consideration into a crucial performance determinant amid the explosive growth of artificial intelligence, especially large language models and deep neural networks. This article delves into hierarchical memory systems for AI workloads, revealing how strategically arranged memory technologies balance speed, capacity, efficiency, and cost. Spanning from lightning-fast registers to massive persistent storage, the discussion highlights specialized AI enhancements: integrated on-chip buffers, high-bandwidth memory configurations, seamless unifie

APA, Harvard, Vancouver, ISO, and other styles

33

Ahn, Minseon, Thomas Willhalm, Norman May, et al. "An Examination of CXL Memory Use Cases for In-Memory Database Management Systems Using SAP HANA." Proceedings of the VLDB Endowment 17, no. 12 (2024): 3827–40. http://dx.doi.org/10.14778/3685800.3685809.

Full text

Abstract:

CXL-based disaggregated memory systems offer options to expand the memory beyond the limits of a single server via cache-coherent memory expansion cards or memory pools. Especially, In-Memory Database Management Systems (IMDBMSs) can benefit from alleviating two critical constraints: (1) limited memory capacity in a server and (2) long restart time during failover to reload data to memory. However, the usage and effectiveness of CXL memory in enterprise-scale IMDBMSs has yet to be validated. In this work---for the first time---we investigate dynamic memory expansion employing commercial CXL me

APA, Harvard, Vancouver, ISO, and other styles

34

Peters, Adaranijo, George Oikonomou, and Georgios Zervas. "In Compute/Memory Dynamic Packet/Circuit Switch Placement for Optically Disaggregated Data Centers." Journal of Optical Communications and Networking 10, no. 7 (2018): B164. http://dx.doi.org/10.1364/jocn.10.00b164.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Kraska, Tim. "Technical Perspective for Sherman: A Write-Optimized Distributed B+Tree Index on Disaggregated Memory." ACM SIGMOD Record 52, no. 1 (2023): 44. http://dx.doi.org/10.1145/3604437.3604447.

Full text

Abstract:

Separation of compute and storage has become the defacto standard for cloud database systems. First proposed in 2007 for database systems [2], it is now widely adopted by all major cloud providers such as Amazon Redshift, Google BigQuery, and Snowflake. Separation of compute and storage adds enormous value for the customer. Users can scale storage independently of compute, which enables them to only pay for what they really uses. Consider a scenario in which data grows linearly over time, but most queries only access the last month of data, which remains relatively stable. Without the separati

APA, Harvard, Vancouver, ISO, and other styles

36

Wu, Chenyuan, Mohammad Javad Amiri, Jared Asch, Heena Nagda, Qizhen Zhang, and Boon Thau Loo. "FlexChain." Proceedings of the VLDB Endowment 16, no. 1 (2022): 23–36. http://dx.doi.org/10.14778/3561261.3561264.

Full text

Abstract:

While permissioned blockchains enable a family of data center applications, existing systems suffer from imbalanced loads across compute and memory, exacerbating the underutilization of cloud resources. This paper presents FlexChain , a novel permissioned blockchain system that addresses this challenge by physically disaggregating CPUs, DRAM, and storage devices to process different blockchain workloads efficiently. Disaggregation allows blockchain service providers to upgrade and expand hardware resources independently to support a wide range of smart contracts with diverse CPU and memory dem

APA, Harvard, Vancouver, ISO, and other styles

37

Zervas, Georgios, Hui Yuan, Arsalan Saljoghei, Qianqiao Chen, and Vaibhawa Mishra. "Optically Disaggregated Data Centers With Minimal Remote Memory Latency: Technologies, Architectures, and Resource Allocation [Invited]." Journal of Optical Communications and Networking 10, no. 2 (2018): A270. http://dx.doi.org/10.1364/jocn.10.00a270.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Alonso, Andrés M., Francisco J. Nogales, and Carlos Ruiz. "A Single Scalable LSTM Model for Short-Term Forecasting of Massive Electricity Time Series." Energies 13, no. 20 (2020): 5328. http://dx.doi.org/10.3390/en13205328.

Full text

Abstract:

Most electricity systems worldwide are deploying advanced metering infrastructures to collect relevant operational data. In particular, smart meters allow tracking electricity load consumption at a very disaggregated level and at high frequency rates. This data opens the possibility of developing new forecasting models with a potential positive impact on electricity systems. We present a general methodology that can process and forecast many smart-meter time series. Instead of using traditional and univariate approaches, we develop a single but complex recurrent neural-network model with long

APA, Harvard, Vancouver, ISO, and other styles

39

Apergis, Nicholas, and Chris Tsoumas. "Long memory and disaggregated energy consumption: Evidence from fossils, coal and electricity retail in the U.S." Energy Economics 34, no. 4 (2012): 1082–87. http://dx.doi.org/10.1016/j.eneco.2011.09.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Matindife, L., Y. Sun, and Z. Wang. "Few-Shot Learning for Image-Based Nonintrusive Appliance Signal Recognition." Computational Intelligence and Neuroscience 2022 (August 23, 2022): 1–14. http://dx.doi.org/10.1155/2022/2142935.

Full text

Abstract:

In this article, we present the recognition of nonintrusive disaggregated appliance signals through a reduced dataset computer vision deep learning approach. Deep learning data requirements are costly in terms of acquisition time, storage memory requirements, computation time, and dynamic memory usage. We develop our recognition strategy on Siamese and prototypical reduced data few-shot classification algorithms. Siamese networks address the 1-shot recognition well. Appliance activation periods vary considerably, and this can result in imbalance in the number of appliance-specific generated si

APA, Harvard, Vancouver, ISO, and other styles

41

Lean, Hooi Hooi, and Russell Smyth. "Long memory in US disaggregated petroleum consumption: Evidence from univariate and multivariate LM tests for fractional integration." Energy Policy 37, no. 8 (2009): 3205–11. http://dx.doi.org/10.1016/j.enpol.2009.04.017.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Ziegler, Tobias, Jacob Nelson-Slivon, Viktor Leis, and Carsten Binnig. "Design Guidelines for Correct, Efficient, and Scalable Synchronization using One-Sided RDMA." Proceedings of the ACM on Management of Data 1, no. 2 (2023): 1–26. http://dx.doi.org/10.1145/3589276.

Full text

Abstract:

Remote data structures built with one-sided Remote Direct Memory Access (RDMA) are at the heart of many disaggregated database management systems today. Concurrent access to these data structures by thousands of remote workers necessitates a highly efficient synchronization scheme. Remarkably, our investigation reveals that existing synchronization schemes display substantial variations in performance and scalability. Even worse, some schemes do not correctly synchronize, resulting in rare and hard-to-detect data corruption. Motivated by these observations, we conduct the first comprehensive a

APA, Harvard, Vancouver, ISO, and other styles

43

Zhang, Yingqiang, Chaoyi Ruan, Cheng Li, et al. "Towards cost-effective and elastic cloud database deployment via memory disaggregation." Proceedings of the VLDB Endowment 14, no. 10 (2021): 1900–1912. http://dx.doi.org/10.14778/3467861.3467877.

Full text

Abstract:

It is challenging for cloud-native relational databases to meet the ever-increasing needs of scaling compute and memory resources independently and elastically. The recent emergence of memory disaggregation architecture, relying on high-speed RDMA network, offers opportunities to build cost-effective and elastic cloud-native databases. There exist proposals to let unmodified applications run transparently on disaggregated systems. However, running relational database kernel atop such proposals experiences notable performance degradation and time-consuming failure recovery, offsetting the benef

APA, Harvard, Vancouver, ISO, and other styles

44

Thakkar, Viraj, Dongha Kim, Yingchun Lai, Hokeun Kim, and Zhichao Cao. "SHIELD: Encrypting Persistent Data of LSM-KVS from Monolithic to Disaggregated Storage." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–28. https://doi.org/10.1145/3725354.

Full text

Abstract:

Log-Structured Merge-tree-based Key-Value Stores (LSM-KVS) are widely used to support modern, high-performance, data-intensive applications. In recent years, with the trend of deploying and optimizing LSM-KVS from monolith to Disaggregated Storage (DS) setups, the confidentiality of LSM-KVS persistent data (e.g., WAL and SST files) is vulnerable to unauthorized access from insiders and external attackers and must be protected using encryption. Existing solutions lack a high-performance design for encryption in LSM-KVS, often focus on in-memory data protection with overheads of 3.4-32.5x, and l

APA, Harvard, Vancouver, ISO, and other styles

45

Hertel, Katarzyna, and Agnieszka Leszczyńska. "Uporczywość inflacji i jej komponentów – badanie empiryczne dla Polski." Przegląd Statystyczny. Statistical Review 2013, no. 2 (2013): 187–210. http://dx.doi.org/10.59139/ps.2013.02.2.

Full text

Abstract:

The paper aims to evaluate inflation persistence at a disaggregated level. The measures of inflation persistence used in the exercise rely solely on time series methods of AR and long memory models (cf: Marques, 2004; Pivetta, Reis, 2007; Baillie, 1996) and are applied to Polish CPI and its 11 components. The choice between those two frameworks has been based on the results of the FDF test (Dolado, Gonzalo, Mayoral, 2006). The second part of the study consisted in investigation of the dynamics of persistence. An experiment of rolling window regressions revealed a decrease in the persistence of

APA, Harvard, Vancouver, ISO, and other styles

46

Stavrakakis, Dimitrios, Dimitra Giantsidi, Maurice Bailleu, Philip Sändig, Shady Issa, and Pramod Bhatotia. "Anchor: A Library for Building Secure Persistent Memory Systems." Proceedings of the ACM on Management of Data 1, no. 4 (2023): 1–31. http://dx.doi.org/10.1145/3626718.

Full text

Abstract:

Cloud infrastructure is experiencing a shift towards disaggregated setups, especially with the introduction of the Compute Express Link (CXL) technology, where byte-addressable ersistent memory (PM) is becoming prominent. To fully utilize the potential of such devices, it is a necessity to access them through network stacks with equivalently high levels of performance (e.g., kernel-bypass, RDMA). While, these advancements are enabling the development of high-performance data management systems, their deployment on untrusted cloud environments also increases the security threats. To this end, w

APA, Harvard, Vancouver, ISO, and other styles

47

Kabić, Marko, Shriram Chandran, and Gustavo Alonso. "Maximus: A Modular Accelerated Query Engine for Data Analytics on Heterogeneous Systems." Proceedings of the ACM on Management of Data 3, no. 3 (2025): 1–25. https://doi.org/10.1145/3725324.

Full text

Abstract:

Several trends are changing the underlying fabric for data processing in fundamental ways. On the hardware side, machines are becoming heterogeneous with smart NICs, TPUs, DPUs, etc., but specially with GPUs taking a more dominant role. On the software side, the diversity in workloads, data sources, and data formats has given rise to the notion of composable data processing where the data is processed across a variety of engines and platforms. Finally, on the infrastructure side, different storage types, disaggregated storage, disaggregated memory, networking, and interconnects are all rapidly

APA, Harvard, Vancouver, ISO, and other styles

48

Alonso, Gustavo. "Technical perspective." ACM SIGMOD Record 51, no. 1 (2022): 14. http://dx.doi.org/10.1145/3542700.3542704.

Full text

Abstract:

Optimizing data movement has always been one of the key ways to get a data processing system to perform efficiently. Appearing under different disguises as computers evolved over the years, the issue is today as relevant as ever. With the advent of the cloud, data movement has become the bottleneck to address in any data processing system. In the cloud, compute and storage are typically disaggregated, with a network in between. In addition, cloud systems are scale-out, i.e., performance is obtained by parallelizing across machines, which also involves network communication. And while it is pos

APA, Harvard, Vancouver, ISO, and other styles

49

Bairner, Alan. "For a Sociology of Sport." Sociology of Sport Journal 29, no. 1 (2012): 102–17. http://dx.doi.org/10.1123/ssj.29.1.102.

Full text

Abstract:

This essay focuses on some of the main challenges that currently face the sociology of sport, the challenge from the natural sciences, the challenge from mainstream sociology and the challenge which we have set ourselves and which, requires new intellectual innovations of the type discussed in the final sections of this essay. It is vital that the sociology of sport be defended against the tyranny of the natural sciences. This project, however, must not be disaggregated from the requirements to fight for greater acceptance from mainstream sociology and to address our own shortcomings by extend

APA, Harvard, Vancouver, ISO, and other styles

50

Amantegui, Jorge, Hugo Morais, and Lucas Pereira. "Benchmark of Electricity Consumption Forecasting Methodologies Applied to Industrial Kitchens." Buildings 12, no. 12 (2022): 2231. http://dx.doi.org/10.3390/buildings12122231.

Full text

Abstract:

Even though Industrial Kitchens (IKs) are among the highest energy intensity spaces, very little work has been done to forecast their consumption. This work explores the possibility of increasing the accuracy of the consumption forecast in an IK by forecasting disaggregated appliance consumption and comparing these results with the forecast of the total consumption of these appliances (Virtual Aggregate—VA). To do so, three different methods are used: the statistical method (Prophet), classic Machine Learning (ML) method such as random forest (RF), and deep learning (DL) method, namely long sh

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!