[SPONSORED POST] In this paper, Matthew Williams, CTO at Rockport Networks, explains how recent innovations in networking technologies have led to a new network architecture that targets the root causes of HPC network congestion. Congestion can delay workload completion times for crucial scientific and enterprise workloads, making HPC systems unpredictable and leaving high-cost cluster resources waiting for delayed data to arrive. Despite various brute-force attempts to resolve the congestion issue, the problem has persisted. Until now.
It’s Time to Resolve the Root Cause of Congestion
Today, every high-performance computing (HPC) workload running globally faces the same crippling issue: Congestion in the network.
Congestion can delay workload completion times for crucial scientific and enterprise workloads, making HPC systems unpredictable and leaving high-cost cluster resources waiting for delayed data to arrive. Despite various brute-force attempts to resolve the congestion issue, the problem has persisted. Until now.
In this paper, Matthew Williams, CTO at Rockport Networks, explains how recent innovations in networking technologies have led to a new network architecture that targets the root causes of HPC network congestion, specifically:
– Why today’s network architectures are not a sustainable approach to HPC workloads
– How HPC workload congestion and latency issues are directly tied to the network architecture
– Why a direct interconnect network architecture minimizes congestion and tail latency
Network Switch Configuration with Dell EMC Ready Nodes
Storage networks are constantly evolving. From traditional Fibre Channel to IP-based storage networks, each technology has its place in the data center. IP-based storage solutions have two main network topologies to choose from based on the technology and administration requirements. Dedicated storage network topology, shared leaf-spine network, software defined storage, and iSCSI SAN are all supported. Hybrid network architectures are common, but add to the complexity.