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Modern computing workloads commonly involve matrix-matrix multiplication (mmul) as a core computing pattern. Coarse-Grained Reconfigurable Arrays (CGRAs) can flexibly and efficiently support it, since they combine operation-level…

Hardware Architecture · Computer Science 2026-04-29 Yuxuan Wang , María José Belda , Fernando Castro , Katzalin Olcoz , David Atienza , Giovanni Ansaloni

Centralized radio access network architectures consolidate the baseband operation towards a cloud-based platform, thereby allowing for efficient utilization of computing assets, effective inter-cell coordination, and exploitation of global…

Networking and Internet Architecture · Computer Science 2014-07-09 Matthew C. Valenti , Salvatore Talarico , Peter Rost

Kernel methods provide an elegant and principled approach to nonparametric learning, but so far could hardly be used in large scale problems, since na\"ive implementations scale poorly with data size. Recent advances have shown the benefits…

Machine Learning · Computer Science 2020-11-30 Giacomo Meanti , Luigi Carratino , Lorenzo Rosasco , Alessandro Rudi

Network Coding (NC) shows great potential in various communication scenarios through changing the packet forwarding principles of current networks. It can improve not only throughput, latency, reliability and security but also alleviates…

Networking and Internet Architecture · Computer Science 2016-01-14 Dávid Szabó , Attila Csoma , Péter Megyesi , András Gulyás , Frank H. P. Fitzek

We observe that emerging artificial intelligence, high-performance computing, and storage workloads pose new challenges for large-scale datacenter networking. RDMA over Converged Ethernet (RoCE) was an attempt to adopt modern Remote Direct…

Deep Convolutional Neural Networks (CNNs) are widely employed in modern computer vision algorithms, where the input image is convolved iteratively by many kernels to extract the knowledge behind it. However, with the depth of convolutional…

Computer Vision and Pattern Recognition · Computer Science 2018-04-11 Chih-Ting Liu , Yi-Heng Wu , Yu-Sheng Lin , Shao-Yi Chien

Neural network compression empowers the effective yet unwieldy deep convolutional neural networks (CNN) to be deployed in resource-constrained scenarios. Most state-of-the-art approaches prune the model in filter-level according to the…

Computer Vision and Pattern Recognition · Computer Science 2019-06-26 Wenxiao Wang , Cong Fu , Jishun Guo , Deng Cai , Xiaofei He

Cloud database systems, particularly their middleware and query execution layers, use sorting as a core operation in query processing, indexing and join execution. Distribution-dependence and limited parallelism are key issues inherent in…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-13 Michael Dang'ana

The advent of RoCE (RDMA over Converged Ethernet) has led to a significant increase in the use of RDMA in datacenter networks. To achieve good performance, RoCE requires a lossless network which is in turn achieved by enabling Priority Flow…

Networking and Internet Architecture · Computer Science 2018-06-22 Radhika Mittal , Alexander Shpiner , Aurojit Panda , Eitan Zahavi , Arvind Krishnamurthy , Sylvia Ratnasamy , Scott Shenker

Achieving highly reliable networks is essential for network operators to ensure proper packet delivery in the event of software errors or hardware failures. Networks must ensure reachability and routing correctness, such as subnet isolation…

Networking and Internet Architecture · Computer Science 2022-01-14 Shenshen Chen , Geng Li , Dennis Duan , Kerim Gokarslan , Bin Li , Qiao Xiang , Haitao Yu , Franck Le , Richard Yang , Ying Zhang

Developers of networked systems often work with low-level RDMA libraries to tailor network modules to take full advantage of offload capabilities offered by RDMA-capable network controllers. Because of the huge design space of networked…

Networking and Internet Architecture · Computer Science 2022-12-22 Konstantin Taranov , Fabian Fischer , Torsten Hoefler

Efficient GPU execution of convolution operators is governed by memory-access efficiency, on-chip data reuse, and execution mapping rather than arithmetic throughput alone. This paper presents a controlled operator-level study of CUDA…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-30 Huriyeh Babak , Melanie Schaller

Automatically tuning parallel compute kernels allows libraries and frameworks to achieve performance on a wide range of hardware, however these techniques are typically focused on finding optimal kernel parameters for particular input sizes…

Performance · Computer Science 2020-09-01 John Lawson

Performance is an important non-functional aspect of the software requirement. Modern software systems are highly-configurable and misconfigurations may easily cause performance issues. A software system that suffers performance issues may…

Software Engineering · Computer Science 2020-10-06 Xue Han , Tingting Yu

To witness quantum advantages in practical settings, substantial efforts are required not only at the hardware level but also on theoretical research to reduce the computational cost of a given protocol. Quantum computation has the…

Quantum Physics · Physics 2021-09-24 Daniel K. Park , Carsten Blank , Francesco Petruccione

Full-system simulation of computer systems is critical to capture the complex interplay between various hardware and software components in future systems. Modeling the network subsystem is indispensable to the fidelity of the full-system…

Hardware Architecture · Computer Science 2023-01-31 Siddharth Agarwal , Minwoo Lee , Ren Wang , Mohammad Alian

Parallel transmission, as defined in high-speed Ethernet standards, enables to use less expensive optoelectronics and offers backwards compatibility with legacy Optical Transport Network (OTN) infrastructure. However, optimal parallel…

Networking and Internet Architecture · Computer Science 2013-04-03 Xiaomin Chen , Admela Jukan , Muriel Médard

As parallelism becomes critically important in the semiconductor technology, high-performance computing, and cloud applications, parallel network systems will increasingly follow suit. Today, parallelism is an essential architectural…

Performance · Computer Science 2017-07-11 Anna Engelmann , Wolfgang Bziuk , Admela Jukan , Muriel Medard

RDMA is an exciting technology that enables a host to access the memory of a remote host without involving the remote CPU. Prior work shows how to use RDMA to improve the performance of distributed in-memory storage systems. However, RDMA…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-08 Stanko Novakovic , Yizhou Shan , Aasheesh Kolli , Michael Cui , Yiying Zhang , Haggai Eran , Liran Liss , Michael Wei , Dan Tsafrir , Marcos Aguilera

High throughput and low latency data processing is essential for systems requiring live decision making, control, and machine learning-optimized data reduction. We focus on two distinct use cases for in-flight streaming data processing for…

Instrumentation and Detectors · Physics 2023-02-14 Jack Hirschman , Andrei Kamalov , Razib Obaid , Finn H. O'Shea , Ryan N Coffee