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1
Intro
2
High Performance Computing (HPC)
3
Artificial Intelligence (AI)
4
AI & HPC - Network Considerations
5
Remote Direct Memory Access - RDMA
6
OVN Kubernetes
7
Single Root I/O Virtualization (SR-IOV)
8
Legacy OVS / OVN Challenges
9
Lab Set-Up: K8s Bare Metal
10
Lab Set-Up: K8s Over OpenStack VM
11
Test Scenarios
12
Iperf 2 - TCP Throughput Benchmark
13
Calico vs Acc OVN: CPU load during test
14
Accelerated OVN: Flow offloads during test
15
Intel MPI Benchmarks - PingPong
16
Computational Fluid Dynamics - OpenFOAM
17
Genome Sequencing - Basecalling benchmark
Description:
Explore five ways to implement Container Network Interface (CNI) for performance-intensive Kubernetes workloads in this 36-minute conference talk. Delve into the evolving landscape of Kubernetes networking, focusing on recent innovations that have improved performance for demanding scientific computing and distributed machine learning applications. Learn about different CNI architectures and technologies, their claimed performance advantages, and how to distinguish between them using real-world benchmarks. Gain insights into network considerations for High Performance Computing (HPC) and Artificial Intelligence (AI) workloads, including Remote Direct Memory Access (RDMA), OVN Kubernetes, and Single Root I/O Virtualization (SR-IOV). Examine lab setups, test scenarios, and performance comparisons using tools like Iperf 2, Intel MPI Benchmarks, OpenFOAM for Computational Fluid Dynamics, and genome sequencing basecalling benchmarks.

Five Ways to Understand Kubernetes Networking for Performance-Intensive Workloads

CNCF [Cloud Native Computing Foundation]
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