A survey on in-network computing: Programmable data plane and technology specific applications

S Kianpisheh, T Taleb - IEEE Communications Surveys & …, 2022 - ieeexplore.ieee.org
In comparison with cloud computing, edge computing offers processing at locations closer to
end devices and reduces the user experienced latency. The new recent paradigm of in …

The future of FPGA acceleration in datacenters and the cloud

C Bobda, JM Mbongue, P Chow, M Ewais… - ACM Transactions on …, 2022 - dl.acm.org
In this article, we survey existing academic and commercial efforts to provide Field-
Programmable Gate Array (FPGA) acceleration in datacenters and the cloud. The goal is a …

Offloading distributed applications onto smartnics using ipipe

M Liu, T Cui, H Schuh, A Krishnamurthy… - Proceedings of the …, 2019 - dl.acm.org
Emerging Multicore SoC SmartNICs, enclosing rich computing resources (eg, a multicore
processor, onboard DRAM, accelerators, programmable DMA engines), hold the potential to …

Serverless computing on heterogeneous computers

D Du, Q Liu, X Jiang, Y Xia, B Zang… - Proceedings of the 27th …, 2022 - dl.acm.org
Existing serverless computing platforms are built upon homogeneous computers, limiting the
function density and restricting serverless computing to limited scenarios. We introduce …

The programmable data plane: Abstractions, architectures, algorithms, and applications

O Michel, R Bifulco, G Retvari, S Schmid - ACM Computing Surveys …, 2021 - dl.acm.org
Programmable data plane technologies enable the systematic reconfiguration of the low-
level processing steps applied to network packets and are key drivers toward realizing the …

hXDP: Efficient software packet processing on FPGA NICs

MS Brunella, G Belocchi, M Bonola… - Communications of the …, 2022 - dl.acm.org
The network interface cards (NICs) of modern computers are changing to adapt to faster
data rates and to help with the scaling issues of general-purpose CPU technologies. Among …

[HTML][HTML] Applications and techniques for fast machine learning in science

AMC Deiana, N Tran, J Agar, M Blott… - Frontiers in big …, 2022 - frontiersin.org
In this community review report, we discuss applications and techniques for fast machine
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …

StRoM: smart remote memory

D Sidler, Z Wang, M Chiosa, A Kulkarni… - Proceedings of the …, 2020 - dl.acm.org
Big data applications often incur large costs in I/O, data transfer and copying overhead,
especially when operating in cloud environments. Since most such computations are …

ghost: Fast & flexible user-space delegation of linux scheduling

JT Humphries, N Natu, A Chaugule, O Weisse… - Proceedings of the …, 2021 - dl.acm.org
We present ghOSt, our infrastructure for delegating kernel scheduling decisions to
userspace code. ghOSt is designed to support the rapidly evolving needs of our data center …

{FUSEE}: A fully {Memory-Disaggregated}{Key-Value} store

J Shen, P Zuo, X Luo, T Yang, Y Su, Y Zhou… - … USENIX Conference on …, 2023 - usenix.org
Distributed in-memory key-value (KV) stores are embracing the disaggregated memory (DM)
architecture for higher resource utilization. However, existing KV stores on DM employ …