標(biāo)題: Titlebook: Network and Parallel Computing; 15th IFIP WG 10.3 In Feng Zhang,Jidong Zhai,Mateo Valero Conference proceedings 2018 IFIP International Fed [打印本頁] 作者: 弄碎 時間: 2025-3-21 17:33
書目名稱Network and Parallel Computing影響因子(影響力)
書目名稱Network and Parallel Computing影響因子(影響力)學(xué)科排名
書目名稱Network and Parallel Computing網(wǎng)絡(luò)公開度
書目名稱Network and Parallel Computing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Network and Parallel Computing被引頻次
書目名稱Network and Parallel Computing被引頻次學(xué)科排名
書目名稱Network and Parallel Computing年度引用
書目名稱Network and Parallel Computing年度引用學(xué)科排名
書目名稱Network and Parallel Computing讀者反饋
書目名稱Network and Parallel Computing讀者反饋學(xué)科排名
作者: Pathogen 時間: 2025-3-22 00:10 作者: 妨礙議事 時間: 2025-3-22 02:27 作者: Eviction 時間: 2025-3-22 06:25 作者: 尖叫 時間: 2025-3-22 12:15
CNLoc: Channel State Information Assisted Indoor WLAN Localization Using Nomadic Access Points,ncertainty of nomadic APs. Our implementation and evaluation show that CNLoc can improve the accuracy with unknown location information of nomadic APs. We also discuss some open issues and new possibilities in future nomadic AP based indoor localization.作者: 頌揚國家 時間: 2025-3-22 14:05
ALOR: Adaptive Layout Optimization of Raft Groups for Heterogeneous Distributed Key-Value Stores,. and .. We conducted experiments on a practical heterogeneous cluster, and the results indicate that, on average, ALOR improves throughput by 36.89%, reduces latency and 99th percentile tail latency by 24.54% and 21.32%, respectively.作者: notion 時間: 2025-3-22 18:47 作者: prosthesis 時間: 2025-3-22 22:27
GPU-Accelerated Clique Tree Propagation for Pouch Latent Tree Models,each model structure during PLTM training. Our experiments with real-world data sets show that the GPU-accelerated implementation procedure can achieve up?to 52x speedup over the sequential implementation running on CPUs. The experiment results signify promising potential for further improvement on the full training of PLTMs with GPUs.作者: minaret 時間: 2025-3-23 04:46 作者: Basal-Ganglia 時間: 2025-3-23 06:59
Data Fine-Pruning: A Simple Way to Accelerate Neural Network Training,g approach. Extensive experiments with different neural networks are conducted to verify the effectiveness of our method. The experimental results show that applying the data fine-pruning approach can reduce the training time by around 14.29% while maintaining the accuracy of the neural network.作者: 平淡而無味 時間: 2025-3-23 12:30 作者: AND 時間: 2025-3-23 13:57 作者: covert 時間: 2025-3-23 21:55 作者: 純樸 時間: 2025-3-24 00:41
0302-9743 ns. The papers cover traditional areas of network and parallel computing, including parallel applications, distributed algorithms, parallel architectures, software environments, and distributed tools..978-3-030-05676-6978-3-030-05677-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: chronicle 時間: 2025-3-24 02:52 作者: 雪崩 時間: 2025-3-24 08:16 作者: Communicate 時間: 2025-3-24 11:28
DLIR: An Intermediate Representation for Deep Learning Processors,dge the gap between DL frameworks and DLPs. DLIR is a tensor-based language with built-in tensor intrinsics that can be directly mapped to hardware primitives. We show that DLIR allows better developing efficiency and is able to generate efficient code.作者: CHURL 時間: 2025-3-24 15:56 作者: Accessible 時間: 2025-3-24 20:05
978-3-030-05676-6IFIP International Federation for Information Processing 2018作者: 別炫耀 時間: 2025-3-25 02:52 作者: lattice 時間: 2025-3-25 04:49 作者: PANIC 時間: 2025-3-25 09:52
https://doi.org/10.1007/978-3-030-05677-3artificial intelligence; cloud computing; clustering; computer architecture; computer networks; computer 作者: N防腐劑 時間: 2025-3-25 13:43
FSObserver: A Performance Measurement and Monitoring Tool for Distributed Storage Systems,sed on the message analysis, named FSObserver, which can accurately and fine-grained trace individual request or response by observing network traffic. Experiments results show that our approach can get accurate performance with slight performance degradation.作者: 隼鷹 時間: 2025-3-25 16:42 作者: 帳單 時間: 2025-3-25 21:00 作者: 窗簾等 時間: 2025-3-26 03:24
ALOR: Adaptive Layout Optimization of Raft Groups for Heterogeneous Distributed Key-Value Stores, node hardware configuration for the underlying cluster and thus adopt even data distribution schemes. However, today’s distributed systems tend to be heterogeneous in nodes’ I/O devices due to the regular worn I/O device replacement and the emergence of expensive new storage media (e.g., non-volati作者: 緩和 時間: 2025-3-26 07:43
STrieGD: A Sampling Trie Indexed Compression Algorithm for Large-Scale Gene Data, of compression algorithms have been developed. However, currently used algorithms fail to simultaneously achieve high compression ratio as well as high compression speed. We propose an algorithm STrieGD that is based on a trie index structure for improving the compression speed of FASTQ files. To r作者: CRAFT 時間: 2025-3-26 09:21 作者: 西瓜 時間: 2025-3-26 13:53
An Efficient Method for Determining Full Point-to-Point Latency of Arbitrary Indirect HPC Networks,eling, link-failure detection, and application optimization. However, it is often hard to determine the full-scale point-to-point latency of large scale HPC networks since it often requires measurements to the square of the number of terminal nodes. In this paper, we propose an efficient method to g作者: AER 時間: 2025-3-26 20:21
KT-Store: A Key-Order and Write-Order Hybrid Key-Value Store with High Write and Range-Query Perforlability. There are two types of data organization in current KV stores: . layout and . layout, which organize records according to key order and write sequence, respectively. While the former and the latter layouts deliver high throughput for range-query and write operations respectively, neither o作者: OGLE 時間: 2025-3-27 01:01
GRAM: A GPU-Based Property Graph Traversal and Query for HPC Rich Metadata Management,ent variables, and the parameters of all executions, etc. Recent studies have shown the feasibility of using property graph to model rich metadata and utilizing graph traversal to query rich metadata stored in the property graph. We propose to utilize GPU to process the rich metadata graphs. There a作者: 哀悼 時間: 2025-3-27 04:02 作者: GROUP 時間: 2025-3-27 05:22
HPC-SFI: System-Level Fault Injection for High Performance Computing Systems,arious kinds of techniques have been proposed, such as hardware-level fault-tolerance, checkpointing, replication, algorithm-base fault-tolerance, etc. There are also many software systems to monitor and handle system-failures, e.g. management and job-scheduling system of HPC systems. To evaluate th作者: saturated-fat 時間: 2025-3-27 11:32
Data Fine-Pruning: A Simple Way to Accelerate Neural Network Training, loss trend of the training data during the training process. We find that given a fixed set of hyper-parameters, pruning specific types of training data can reduce the time consumption of the training process while maintaining the accuracy of the neural network. We developed a data fine-pruning app作者: 流利圓滑 時間: 2025-3-27 15:40
Balancing the QOS and Security in Dijkstra Algorithm by SDN Technology,eatures of the network routing area using software defined networks (SDN). The SDN framework enables an efficient decoupled implementation of dynamic routing protocols which could aware the communication network status. In this work we consider the varying delay status of the communication network a作者: 做方舟 時間: 2025-3-27 20:49
Labeled Network Stack: A Co-designed Stack for Low Tail-Latency and High Concurrency in Datacenter pays more attention to throughput and average performance, considering little on tail latency and priority. We address this question by proposing a hardware-software co-designed Labeled Network Stack (LNS) for future datacenters. The key innovation is a payload labeling mechanism that distinguishes 作者: DIS 時間: 2025-3-28 01:50 作者: Awning 時間: 2025-3-28 05:28 作者: DEI 時間: 2025-3-28 06:48 作者: 熱烈的歡迎 時間: 2025-3-28 12:53 作者: jovial 時間: 2025-3-28 14:59 作者: mechanism 時間: 2025-3-28 21:10 作者: 瑣碎 時間: 2025-3-29 01:58
DLIR: An Intermediate Representation for Deep Learning Processors,eep learning algorithms. However, the learning cost of mastering these DLPs is high as they use different programming interfaces. On the other hand, many deep learning frameworks are proposed to ease the burden of developing deep learning algorithms, but few of them support DLPs. Due to the special 作者: resistant 時間: 2025-3-29 06:25
ep detail essential for reproducible results.Contains key no.Featuring a diverse array of model organisms and scientific techniques, .Sirtuins: Methods and Protocols. collects detailed contributions from experts in the field addressing this vital family of genes. Opening with methods to generate sir作者: 配置 時間: 2025-3-29 08:28 作者: 用手捏 時間: 2025-3-29 13:35
Yangyang Wang,Yunpeng Chai,Xin Wangep detail essential for reproducible results.Contains key no.Featuring a diverse array of model organisms and scientific techniques, .Sirtuins: Methods and Protocols. collects detailed contributions from experts in the field addressing this vital family of genes. Opening with methods to generate sir作者: Kinetic 時間: 2025-3-29 15:56
Yanzhen Gao,Xiaozhen Bao,Jing Xing,Zheng Wei,Jie Ma,Peiheng Zhangep detail essential for reproducible results.Contains key no.Featuring a diverse array of model organisms and scientific techniques, .Sirtuins: Methods and Protocols. collects detailed contributions from experts in the field addressing this vital family of genes. Opening with methods to generate sir作者: fluffy 時間: 2025-3-29 19:57 作者: emulsify 時間: 2025-3-30 01:34 作者: geriatrician 時間: 2025-3-30 04:32
Haobo Wang,Yinliang Yue,Shuibing He,Weiping Wangep detail essential for reproducible results.Contains key no.Featuring a diverse array of model organisms and scientific techniques, .Sirtuins: Methods and Protocols. collects detailed contributions from experts in the field addressing this vital family of genes. Opening with methods to generate sir作者: SPALL 時間: 2025-3-30 09:18 作者: 只有 時間: 2025-3-30 12:26 作者: chisel 時間: 2025-3-30 18:33 作者: ESO 時間: 2025-3-31 00:40
Junyu Li,Ligang He,Shenyuan Ren,Rui Maoep detail essential for reproducible results.Contains key no.Featuring a diverse array of model organisms and scientific techniques, .Sirtuins: Methods and Protocols. collects detailed contributions from experts in the field addressing this vital family of genes. Opening with methods to generate sir作者: Generosity 時間: 2025-3-31 03:21 作者: 拋射物 時間: 2025-3-31 06:46 作者: progestin 時間: 2025-3-31 11:09
Peng Jiang,Ligang He,Shenyuan Ren,Junyu Li,Yuhua Cuiete di pixel tra loro connessi che si sviluppa nel tempo, tramite operazioni locali, deterministiche e iterative. L‘immagine cosi‘ trasformata puo‘ mostrare, in uno spazio dimensionale più ampio, delle regolarità morfologiche e dinamiche che, nelle dimensioni originarie, sarebbero non visibili oppur作者: Shuttle 時間: 2025-3-31 15:31 作者: mitten 時間: 2025-3-31 21:10
Yi Liu,Yunchun Li,Honggang Zhou,Jingyi Zhang,Hailong Yang,Wei Liete di pixel tra loro connessi che si sviluppa nel tempo, tramite operazioni locali, deterministiche e iterative. L‘immagine cosi‘ trasformata puo‘ mostrare, in uno spazio dimensionale più ampio, delle regolarità morfologiche e dinamiche che, nelle dimensioni originarie, sarebbero non visibili oppur作者: 不要不誠實 時間: 2025-4-1 01:17
Nan Hu,Zhiguang Chen,Yunfei Du,Yutong Lua in una rete di pixel tra loro connessi che si sviluppa nel tempo, tramite operazioni locali, deterministiche e iterative. L‘immagine cosi‘ trasformata puo‘ mostrare, in uno spazio dimensionale più ampio, delle regolarità morfologiche e dinamiche che, nelle dimensioni originarie, sarebbero non visi作者: JAMB 時間: 2025-4-1 04:55
Huiying Lan,Zidong Duete di pixel tra loro connessi che si sviluppa nel tempo, tramite operazioni locali, deterministiche e iterative. L‘immagine cosi‘ trasformata puo‘ mostrare, in uno spazio dimensionale più ampio, delle regolarità morfologiche e dinamiche che, nelle dimensioni originarie, sarebbero non visibili oppur作者: 緊張過度 時間: 2025-4-1 07:48 作者: Coma704 時間: 2025-4-1 11:34
GRAM: A GPU-Based Property Graph Traversal and Query for HPC Rich Metadata Management,store properties. In addition, we propose two new optimizations, parallel filtering and basic operations merging, to accelerate the metadata graph traversal. Our evaluation results show that GRAM can be effectively applied to user scenarios in HPC systems, and the performance of metadata management
