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Federated Learning (FL) is an approach for privacy-preserving Machine Learning (ML), enabling model training across multiple clients without centralized data collection. With an aggregator server coordinating training, aggregating model…

Machine Learning · Computer Science 2025-03-04 Ahmad Faraz Khan , Samuel Fountain , Ahmed M. Abdelmoniem , Ali R. Butt , Ali Anwar

Multiversioning is widely used in databases, transactional memory, and concurrent data structures. It can be used to support read-only transactions that appear atomic in the presence of concurrent update operations. Any system that…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-10 Yuanhao Wei , Guy E. Blelloch , Panagiota Fatourou , Eric Ruppert

Although existing garbage collectors (GCs) perform extremely well on typical programs, there still exist pathological programs for which modern GCs significantly degrade performance. This observation begs the question: might there exist a…

Programming Languages · Computer Science 2025-12-19 Matthew Sotoudeh

Edge caching via the placement of distributed storages throughout the network is a promising solution to reduce latency and network costs of content delivery. With the advent of the upcoming 5G future, billions of F-RAN (Fog-Radio Access…

Networking and Internet Architecture · Computer Science 2020-10-22 Khushal Sethi , Manan Suri

As consumers are increasingly engaged in social networking and E-commerce activities, businesses grow to rely on Big Data analytics for intelligence, and traditional IT infrastructures continue to migrate to the cloud and edge, these trends…

Networking and Internet Architecture · Computer Science 2020-05-25 Vaneet Aggarwal , Tian Lan

This letter proposes a novel three-tier content caching architecture for Vehicular Fog Caching (VFC)-assisted platoon, where the VFC is formed by the vehicles driving near the platoon. The system strategically coordinates storage across…

Networking and Internet Architecture · Computer Science 2026-02-05 Bowen Tan , Qiong Wu , Pingyi Fan , Kezhi Wang , Nan Cheng , Wen Chen

In the field of instruction-following large vision-language models (LVLMs), the efficient deployment of these models faces challenges, notably due to the high memory demands of their key-value (KV) caches. Conventional cache management…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Zuyan Liu , Benlin Liu , Jiahui Wang , Yuhao Dong , Guangyi Chen , Yongming Rao , Ranjay Krishna , Jiwen Lu

Large Language Model (LLM) serving is increasingly constrained by the growing size of the key-value (KV) cache, which scales with both context length and generation length. Prior work shows that attention is dominated by a small subset of…

Machine Learning · Computer Science 2026-04-21 Nazmul Takbir , Hamidreza Alikhani , Nikil Dutt , Sangeetha Abdu Jyothi

Big data analytics frameworks, such as Spark and Giraph, need to process and cache massive amounts of data that do not always fit on the heap. Therefore, frameworks temporarily move long-lived objects outside the managed heap (off-heap) on…

NVMe Flash-based SSDs are widely deployed in data centers to cache working sets of large-scale web services. As data centers face increasing sustainability demands, such as reduced carbon emissions, efficient management of Flash…

Hardware Architecture · Computer Science 2025-03-18 Michael Allison , Arun George , Javier Gonzalez , Dan Helmick , Vikash Kumar , Roshan Nair , Vivek Shah

We describe an efficient and fault-tolerant algorithm for distributed cyclic garbage collection. The algorithm imposes few requirements on the local machines and allows for flexibility in the choice of local collector and distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 N. Allen , T. Terriberry

LLM decoding is bottlenecked for large batches and long contexts by loading the key-value (KV) cache from high-bandwidth memory, which inflates per-token latency, while the sequential nature of decoding limits parallelism. We analyze the…

Machine Learning · Computer Science 2025-05-28 Ted Zadouri , Hubert Strauss , Tri Dao

Federated Continual Learning (FCL) has recently emerged as a crucial research area, as data from distributed clients typically arrives as a stream, requiring sequential learning. This paper explores a more practical and challenging FCL…

Machine Learning · Computer Science 2025-06-17 Minh-Duong Nguyen , Le-Tuan Nguyen , Quoc-Viet Pham

Flash memory is a non-volatile computer memory comprised of blocks of cells, wherein each cell is implemented as either NAND or NOR floating gate. NAND flash is currently the most widely used type of flash memory. In a NAND flash memory,…

Information Theory · Computer Science 2009-11-23 Anxiao , Jiang , Robert Mateescu , Eitan Yaakobi , Jehoshua Bruck , Paul H. Siegel , Alexander Vardy , Jack K. Wolf

NAND flash memory is ubiquitous in everyday life today because its capacity has continuously increased and cost has continuously decreased over decades. This positive growth is a result of two key trends: (1) effective process technology…

Hardware Architecture · Computer Science 2017-09-25 Yu Cai , Saugata Ghose , Erich F. Haratsch , Yixin Luo , Onur Mutlu

With the rapid growth of mobile data traffic and the increasing prevalence of video streaming, proactive content caching in edge computing has become crucial for reducing latency and alleviating network congestion. However, traditional…

Machine Learning · Computer Science 2025-04-09 Rui Wang

Cache plays an important role to maintain high and stable performance (i.e. high throughput, low tail latency and throughput jitter) in storage systems. Existing rule-based cache management methods, coupled with engineers' manual…

Hardware Architecture · Computer Science 2022-03-28 Ji Zhang , Xijun Li , Xiyao Zhou , Mingxuan Yuan , Zhuo Cheng , Keji Huang , Yifan Li

Current portable memory device relies heavily on flash memory technology for its implementation. New generation of non-volatile memory is likely to replace floating gates, charge-trapping memory currently still suffering from inadequate…

Applied Physics · Physics 2023-03-27 Yifan Hu

Storage-class memory (SCM) combines the benefits of a solid-state memory, such as high-performance and robustness, with the archival capabilities and low cost of conventional hard-disk magnetic storage. Among candidate solid-state…

Hardware Architecture · Computer Science 2017-04-19 Wonil Choi , Mohammad Arjomand , Myoungsoo Jung , Mahmut Kandemir

Many cloud applications rely on fast and non-relational storage to aid in the processing of large amounts of data. Managed runtimes are now widely used to support the execution of several storage solutions of the NoSQL movement,…

Programming Languages · Computer Science 2017-04-12 Duarte Patrício , José Simão , Luís Veiga