Offloading machine learning to programmable data planes: A systematic survey
The demand for machine learning (ML) has increased significantly in recent decades,
enabling several applications, such as speech recognition, computer vision, and …
enabling several applications, such as speech recognition, computer vision, and …
In-network aggregation for data center networks: A survey
A Feng, D Dong, F Lei, J Ma, E Yu, R Wang - Computer Communications, 2023 - Elsevier
Aggregation applications are widely deployed in data centers, such as distributed machine
learning and MapReduce-like framework. These applications typically have large …
learning and MapReduce-like framework. These applications typically have large …
{CASSINI}:{Network-Aware} Job Scheduling in Machine Learning Clusters
We present CASSINI, a network-aware job scheduler for machine learning (ML) clusters.
CASSINI introduces a novel geometric abstraction to consider the communication pattern of …
CASSINI introduces a novel geometric abstraction to consider the communication pattern of …
Bitsense: Universal and nearly zero-error optimization for sketch counters with compressive sensing
Sketch algorithms have been widely deployed for network measurement as they achieve
high accuracy with restricted resource usage. They store measurement results compactly in …
high accuracy with restricted resource usage. They store measurement results compactly in …
Clickinc: In-network computing as a service in heterogeneous programmable data-center networks
In-Network Computing (INC) has found many applications for performance boosts or cost
reduction. However, given heterogeneous devices, diverse applications, and multi-path …
reduction. However, given heterogeneous devices, diverse applications, and multi-path …
A2tp: Aggregator-aware in-network aggregation for multi-tenant learning
Distributed Machine Learning (DML) techniques are widely used to accelerate the training of
large-scale machine learning models. However, during training iterations, gradients need to …
large-scale machine learning models. However, during training iterations, gradients need to …
On-fiber photonic computing
In the 1800s, Charles Babbage envisioned computers as analog devices. However, it was
not until 150 years later that a Mechanical Analog Computer was constructed for the US …
not until 150 years later that a Mechanical Analog Computer was constructed for the US …
[HTML][HTML] Robust open-set classification for encrypted traffic fingerprinting
Encrypted network traffic has been known to leak information about their underlying content
through side-channel information leaks. Traffic fingerprinting attacks exploit this by using …
through side-channel information leaks. Traffic fingerprinting attacks exploit this by using …
Roar: A router microarchitecture for in-network allreduce
R Wang, D Dong, F Lei, J Ma, K Wu, K Lu - Proceedings of the 37th …, 2023 - dl.acm.org
The allreduce operation is the most commonly used collective operation in distributed or
parallel applications. It aggregates data collected from distributed hosts and broadcasts the …
parallel applications. It aggregates data collected from distributed hosts and broadcasts the …
Memory management in activermt: Towards runtime-programmable switches
R Das, AC Snoeren - Proceedings of the ACM SIGCOMM 2023 …, 2023 - dl.acm.org
A wide variety of in-network services have been developed for RMT-based switching
hardware, almost exclusively through the P4 language and ecosystem. Many of these …
hardware, almost exclusively through the P4 language and ecosystem. Many of these …