Search results for: machine learning
Training vs Inference – Network Compression
This training versus inference workload series provides platform architects and owners insights about ML workload characteristics. Instead of treating deep neural...
Training vs Inference – Numerical Precision
Part 4 focused on the memory consumption of a CNN and revealed that neural networks require parameter data (weights) and input data...
Training vs Inference – Memory Consumption by Neural Networks
This article dives deeper into the memory consumption of deep learning neural network architectures. What exactly happens when an input is...
vSphere 7 Cores per Socket and Virtual NUMA
Regularly I meet with customers to discuss NUMA technology, and one of the topics that are always on the list is...
Project Monterey and the need for Network Cycles Offload for ML Workloads.
VMworld has started, and that means a lot of new announcements. One of the most significant projects VMware is working on...
PCIe Device NUMA Node Locality
During this Christmas break, I wanted to learn PowerCLI properly. As I’m researching the use-cases of new hardware types and workloads...
Basic Terminologies Large Language Models
Many organizations are in the process of deploying large language models to apply to their use cases. Publically available Large Language...
Sub-NUMA Clustering
I’m noticing a trend that more ESXi hosts have Sub-NUMA Clustering enabled. Typically this setting is used in the High-Performance Computing...