httpv://www.youtube.com/watch?v=6xtUq0p4K_s
In this video, Joel Scherpelz from Nvidia presents: RDMA for Heterogeneous Parallel Computing. Recorded at the Open Fabrics Workshop on March 27, 2012 in Monterey, CA.
httpv://www.youtube.com/watch?v=6xtUq0p4K_s
In this video, Joel Scherpelz from Nvidia presents: RDMA for Heterogeneous Parallel Computing. Recorded at the Open Fabrics Workshop on March 27, 2012 in Monterey, CA.
[SPONSORED GUEST ARTICLE] When it comes to AI and HPC workloads, networking is critical. While this is well known already, the impact your networking fabric performance has on parameters like job completion time can ….
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