19 citations · 45 across the 8 of their papers we have counts for
9 papers
PL2: Towards Predictable Low Latency in Rack-Scale Networks
Yanfang Le, Radhika Niranjan Mysore, Lalith Suresh +4
High performance rack-scale offerings package disaggregated pools of compute, memory and storage hardware in a single rack to run diverse workloads with varying requirements, inclu…
Accelerating Deep Learning Inference via Learned Caches
Arjun Balasubramanian, Adarsh Kumar, Yuhan Liu +3
Deep Neural Networks (DNNs) are witnessing increased adoption in multiple domains owing to their high accuracy in solving real-world problems. However, this high accuracy has been…
Accelerating Deep Learning Inference via Freezing
Adarsh Kumar, Arjun Balasubramanian, Shivaram Venkataraman +1
Over the last few years, Deep Neural Networks (DNNs) have become ubiquitous owing to their high accuracy on real-world tasks. However, this increase in accuracy comes at the cost o…
D2R: Dataplane-Only Policy-Compliant Routing Under Failures
Kausik Subramanian, Anubhavnidhi Abhashkumar, Loris D'Antoni +1
In networks today, the data plane handles forwarding---sending a packet to the next device in the path---and the control plane handles routing---deciding the path of the packet in…
Archipelago: A Scalable Low-Latency Serverless Platform
Arjun Singhvi, Kevin Houck, Arjun Balasubramanian +3
The increased use of micro-services to build web applications has spurred the rapid growth of Function-as-a-Service (FaaS) or serverless computing platforms. While FaaS simplifies…
SNF: Serverless Network Functions
Arjun Singhvi, Junaid Khalid, Aditya Akella +1
It is increasingly common to outsource network functions (NFs) to the cloud. However, no cloud providers offer NFs-as-a-Service (NFaaS) that allows users to run custom NFs. Our wor…