Search Results - "Distributed computing methodologies"

Commodity single board computer clusters and their applications by Johnston, Steven J., Basford, Philip J., Perkins, Colin S., Herry, Herry, Tso, Fung Po, Pezaros, Dimitrios, Mullins, Robert D., Yoneki, Eiko, Cox, Simon J., Singer, Jeremy

“…Current commodity Single Board Computers (SBCs) are sufficiently powerful to run mainstream operating systems and workloads. Many of these boards may be linked…”
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MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems by Hsia, Samuel, Golden, Alicia, Acun, Bilge, Ardalani, Newsha, DeVito, Zachary, Wei, Gu-Yeon, Brooks, David, Wu, Carole-Jean

“…Training and deploying large-scale machine learning models is time-consuming, requires significant distributed computing infrastructures, and incurs high…”
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Overview of fair federated learning for fairness and privacy preservation by Kim, Dohyoung, Oh, Kyoungsu, Lee, Youngho, Woo, Hyekyung

“…In the rapidly advancing field of machine learning, federated learning (FL) has facilitated a paradigm shift, enabling collaborative model development across…”
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Submodularity of Distributed Join Computation by Li, Rundong, Riedewald, Mirek, Deng, Xinyan

“…We study distributed equi-join computation in the presence of join-attribute skew, which causes load imbalance. Skew can be addressed by more fine-grained…”
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Fast and scalable distributed deep convolutional autoencoder for fMRI big data analytics by Makkie, Milad, Huang, Heng, Zhao, Yu, Vasilakos, Athanasios V., Liu, Tianming

“…In recent years, analyzing task-based fMRI (tfMRI) data has become an essential tool for understanding brain function and networks. However, due to the sheer…”
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AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs by Zhang, Ruisi, Javaheripi, Mojan, Ghodsi, Zahra, Bleiweiss, Amit, Koushanfar, Farinaz

“…Distributed GNN training on contemporary massive and densely connected graphs requires information aggregation from all neighboring nodes, which leads to an…”
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Centralized Training and Decentralized Control through the Actor-Critic Paradigm for Highly Optimized Multicores by Dietrich, Benedikt, Khdr, Heba, Henkel, Jorg

“…While distributed, neural-network-based resource controllers represent the state of the art for their ability to cope with the ever-expanding decision space,…”
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HADFL: Heterogeneity-aware Decentralized Federated Learning Framework by Cao, Jing, Lian, Zirui, Liu, Weihong, Zhu, Zongwei, Ji, Cheng

“…Federated learning (FL) supports training models on geographically distributed devices. However, traditional FL systems adopt a centralized synchronous…”
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DeepScaler: Holistic Autoscaling for Microservices Based on Spatiotemporal GNN with Adaptive Graph Learning by Meng, Chunyang, Song, Shijie, Tong, Haogang, Pan, Maolin, Yu, Yang

“…Autoscaling functions provide the foundation for achieving elasticity in the modern cloud computing paradigm. It enables dynamic provisioning or…”
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Katara: synthesizing CRDTs with verified lifting by Laddad, Shadaj, Power, Conor, Milano, Mae, Cheung, Alvin, Hellerstein, Joseph M.

“…Conflict-free replicated data types (CRDTs) are a promising tool for designing scalable, coordination-free distributed systems. However, constructing correct…”
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MMDFL: Multi-Model-based Decentralized Federated Learning for Resource-Constrained AIoT Systems by Yan, Dengke, Yang, Yanxin, Hu, Ming, Fu, Xin, Chen, Mingsong

“…Along with the prosperity of Artificial Intelligence (AI) techniques, more and more Artificial Intelligence of Things (AIoT) applications adopt Federated…”
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Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs by Wang, Pengyu, Li, Chao, Wang, Jing, Wang, Taolei, Zhang, Lu, Leng, Jingwen, Chen, Quan, Guo, Minyi

“…Graph sampling and random walk operations, capturing the structural properties of graphs, are playing an important role today as we cannot directly adopt…”
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Derm: SLA-aware Resource Management for Highly Dynamic Microservices by Chen, Liao, Luo, Shutian, Lin, Chenyu, Mo, Zizhao, Xu, Huanle, Ye, Kejiang, Xu, Chengzhong

“…Ensuring efficient resource allocation while providing service level agreement (SLA) guarantees for end-to-end (E2E) latency is crucial for microservice…”
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Distributed programming using role-parametric session types in go: statically-typed endpoint APIs for dynamically-instantiated communication structures by Castro, David, Hu, Raymond, Jongmans, Sung-Shik, Ng, Nicholas, Yoshida, Nobuko

“…This paper presents a framework for the static specification and safe programming of message passing protocols where the number and kinds of participants are…”
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PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models by Lee, Yunjae, Kim, Hyeseong, Rhu, Minsoo

“…Training recommendation systems (RecSys) faces several challenges as it requires the "data preprocessing" stage to preprocess an ample amount of raw data and…”
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NDFT: Accelerating Density Functional Theory Calculations via Hardware/Software Co-Design on Near-Data Computing System by Jiang, Qingcai, Tu, Buxin, Hao, Xiaoyu, Chen, Junshi, An, Hong

“…Linear-response time-dependent Density Functional Theory (LR-TDDFT) is a widely used method for accurately predicting the excited-state properties of physical…”
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CRDT Emulation, Simulation, and Representation Independence by Liittschwager, Nathan, Castello, Jonathan, Tsampas, Stelios, Kuper, Lindsey

“…Conflict-free replicated data types (CRDTs) are distributed data structures designed for fault tolerance and high availability. CRDTs have historically been…”
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DS-GL: Advancing Graph Learning via Harnessing Nature's Power within Scalable Dynamical Systems by Song, Ruibing, Wu, Chunshu, Liu, Chuan, Li, Ang, Huang, Michael, Geng, Tony Tong

“…With the rapid digitization of the world, an increasing number of real-world applications are turning to non-Euclidean data, modeled as graphs. Due to their…”
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Invited: Waving the Double-Edged Sword: Building Resilient CAVs with Edge and Cloud Computing by Liu, Xiangguo, Luo, Yunpeng, Goeckner, Anthony, Chakraborty, Trishna, Jiao, Ruochen, Wang, Ningfei, Wang, Yixuan, Sato, Takami, Chen, Qi Alfred, Zhu, Qi

“…The rapid advancement of edge and cloud computing platforms, vehicular ad-hoc networks, and machine learning techniques have brought both opportunities and…”
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Addressing Bias and Fairness Using Fair Federated Learning: A Synthetic Review by Kim, Dohyoung, Woo, Hyekyung, Lee, Youngho

“…The rapid increase in data volume and variety within the field of machine learning necessitates ethical data utilization and adherence to strict privacy…”
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