By By Brien Posey09/11/2025
Publication Date: 2025-09-11 00:00:00
How-To
Improving the Performance of AI Workloads
Recently, I have been hard at work on a project related to AI-generated video. Along the way however, I ran into some unexpected performance issues, which I had to solve in a completely counterintuitive way. That being the case, I wanted to share with you my troubleshooting process and the steps that I took to resolve the issue.
So before I get too far into this discussion, let me tell you a little bit about the problem that I encountered. Initially, I made the decision to run the rendering job on a high-end, but consumer-grade PC (all of my enterprise grade hardware was in use at the time). This particular machine is equipped with a current generation Intel I9 CPU, roughly 200 GB of RAM, NVMe storage, and a Nvidia Geforce 4090 GPU. In spite of the machine’s hardware specs however, the estimated completion time for this particular job was about 12 days.
A few days into the job, one of my enterprise-class machines became available. This machine was equipped with a Nvidia A6000 GPU, which is far more capable than the 4090 that I had been using. Needless to say, I expected the job to complete much more quickly on this machine since it was equipped with more powerful hardware and a vastly superior GPU. However, the estimated time of completion for the job running on this machine was 17 days. That’s five days longer than the consumer…
