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Surendra Anubolu

Publications and source records attributed to Surendra Anubolu.

2 recordsLinked to original sources

In-Network Collective Operations: Game Changer or Challenge for AI Workloads?

This paper summarizes the opportunities of in-network collective operations (INC) for accelerated collective operations in AI workloads. We provide sufficient detail to make this important field accessible to non-experts in AI or networking, fostering a connection between these communities. Consider two types of INC: Edge-INC, where the system is implemented at the node level, and Core-INC, where the system is embedded within network switches. We outline the potential performance benefits as well as six key obstacles in the context of both Edge-INC and Core-INC that may hinder their adoption. Finally, we present a set of predictions for the future development and application of INC.

cs.NI

Datacenter Ethernet and RDMA: Issues at Hyperscale

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 Memory Access (RDMA) features into existing Ethernet installations. Now, a decade later, we revisit RoCE's design points and conclude that several of its shortcomings must be addressed to fulfill the demands of hyperscale datacenters. We predict that both the datacenter and high-performance computing markets will converge and adopt modernized Ethernet-based high-performance networking solutions that will replace TCP and RoCE within a decade.

cs.NI