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Summarizing graphs w.r.t. structural features is important to reduce the graph's size and make tasks like indexing, querying, and visualization feasible. Our generic parallel BRS algorithm efficiently summarizes large graphs w.r.t. a custom…

Data Structures and Algorithms · Computer Science 2023-05-16 Jannik Rau , David Richerby , Ansgar Scherp

More and more large data collections are gathered worldwide in various IT systems. Many of them possess the networked nature and need to be processed and analysed as graph structures. Due to their size they require very often usage of…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-06-04 Tomasz Kajdanowicz , Przemyslaw Kazienko , Wojciech Indyk

In this paper, a joint task, spectrum, and transmit power allocation problem is investigated for a wireless network in which the base stations (BSs) are equipped with mobile edge computing (MEC) servers to jointly provide computational and…

Signal Processing · Electrical Eng. & Systems 2020-07-21 Sihua Wang , Mingzhe Chen , Xuanlin Liu , Changchuan Yin , Shuguang Cui , H. Vincent Poor

Partitioning a graph into blocks of roughly equal weight while cutting only few edges is a fundamental problem in computer science with numerous practical applications. While shared-memory parallel partitioners have recently matured to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-06 Peter Sanders , Daniel Seemaier

Retrosynthetic planning, which aims to find a reaction pathway to synthesize a target molecule, plays an important role in chemistry and drug discovery. This task is usually modeled as a search problem. Recently, data-driven methods have…

Artificial Intelligence · Computer Science 2022-06-24 Shufang Xie , Rui Yan , Peng Han , Yingce Xia , Lijun Wu , Chenjuan Guo , Bin Yang , Tao Qin

The paper provides a unified co-design of 1) a programming and execution model that allows spawning tasks from within the vertex data at runtime, 2) language constructs for \textit{actions} that send work to where the data resides,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-09 Bibrak Qamar Chandio , Prateek Srivastava , Maciej Brodowicz , Martin Swany , Thomas Sterling

Computing on encrypted data is a promising approach to reduce data security and privacy risks, with homomorphic encryption serving as a facilitator in achieving this goal. In this work, we accelerate homomorphic operations using the…

Cryptography and Security · Computer Science 2023-10-04 Harshita Gupta , Mayank Kabra , Juan Gómez-Luna , Konstantinos Kanellopoulos , Onur Mutlu

Graph pattern matching algorithms to handle million-scale dynamic graphs are widely used in many applications such as social network analytics and suspicious transaction detections from financial networks. On the other hand, the computation…

Databases · Computer Science 2019-07-10 Hiroki Kanezashi , Toyotaro Suzumura , Dario Garcia-Gasulla , Min-hwan Oh , Satoshi Matsuoka

Betweenness Centrality (BC) is steadily growing in popularity as a metrics of the influence of a vertex in a graph. The BC score of a vertex is proportional to the number of all-pairs-shortest-paths passing through it. However, complete and…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-22 Flavio Vella , Giancarlo Carbone , Massimo Bernaschi

To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors. Traditional…

Signal Processing · Electrical Eng. & Systems 2022-05-10 Qunsong Zeng , Jiawei Liu , Jun Lan , Yi Gong , Zhongrui Wang , Yida Li , Kaibin Huang

We present GraphTensor, a comprehensive open-source framework that supports efficient parallel neural network processing on large graphs. GraphTensor offers a set of easy-to-use programming primitives that appreciate both graph and neural…

Hardware Architecture · Computer Science 2023-05-30 Junhyeok Jang , Miryeong Kwon , Donghyun Gouk , Hanyeoreum Bae , Myoungsoo Jung

Recent progress in Graph Neural Networks (GNNs) for modeling atomic simulations has the potential to revolutionize catalyst discovery, which is a key step in making progress towards the energy breakthroughs needed to combat climate change.…

Machine Learning · Computer Science 2022-04-12 Anuroop Sriram , Abhishek Das , Brandon M. Wood , Siddharth Goyal , C. Lawrence Zitnick

Large-scale federated learning (FL) over wireless multiple access channels (MACs) has emerged as a crucial learning paradigm with a wide range of applications. However, its widespread adoption is hindered by several major challenges,…

Machine Learning · Computer Science 2024-11-01 Vineet Sunil Gattani , Junshan Zhang , Gautam Dasarathy

Graph Neural Networks (GNNs) have become popular across a diverse set of tasks in exploring structural relationships between entities. However, due to the highly connected structure of the datasets, distributed training of GNNs on…

Machine Learning · Computer Science 2025-09-08 Arefin Niam , Tevfik Kosar , M S Q Zulkar Nine

Large matrix multiplication is a cornerstone of modern machine learning workloads, yet traditional approaches suffer from cubic computational complexity (e.g., $\mathcal{O}(n^3)$ for a matrix of size $n\times n$). We present Low-Rank GEMM,…

Performance · Computer Science 2025-11-25 Alfredo Metere

Performance of distributed graph processing systems significantly suffers from 'communication bottleneck' as a large number of messages are exchanged among servers at each step of the computation. Motivated by graph based MapReduce, we…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-11 Saurav Prakash , Amirhossein Reisizadeh , Ramtin Pedarsani , Amir Salman Avestimehr

Optimal power flow (OPF) has been used for real-time grid operations. Prior efforts demonstrated that utilizing flexibility from dynamic topologies will improve grid efficiency. However, this will convert the linear OPF into a mixed-integer…

Systems and Control · Electrical Eng. & Systems 2024-10-24 Thuan Pham , Xingpeng Li

This thesis develops signal-processing algorithms and implementation schemes under constraints of minimal parallelism and memory space, with the goal of improving energy efficiency of low-power computing hardware. We propose (i) a…

Signal Processing · Electrical Eng. & Systems 2025-12-30 Sergey Salishev

The Maximum (Minimum) Leaf Spanning Tree problem asks for a spanning tree with the largest (smallest) number of leaves. As spanning trees are often computed using graph search algorithms, it is natural to restrict this problem to the set of…

Data Structures and Algorithms · Computer Science 2026-04-02 Jesse Beisegel , Ekkehard Köhler , Robert Scheffler , Martin Strehler

Power flow analysis plays a fundamental and critical role in the energy management system (EMS). It is required to well accommodate large and complex power system. To achieve a high performance and accurate power flow analysis, a graph…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-20 Chen Yuan , Yi Lu , Wei Feng , Guangyi Liu , Renchang Dai , Yachen Tang , Zhiwei Wang