Tag: workload

Connected in AI DC

Posted on by lechuck park

This diagram titled “Data is Connected in AI DC” illustrates the relationships starting from workload scheduling in an AI data center.

Key aspects of the diagram:

  1. The entire system’s interconnected relationships begin with workload scheduling.
  2. The diagram divides the process into two major phases:
    • Deterministic phase: Primarily concerned with power requirements that operate in a predictable, planned manner.
    • Statistical phase: Focused on cooling requirements, where predictions vary based on external environmental conditions.
  3. The “Prophet Commander” at the workload scheduling stage can predict/direct future requirements, allowing the system to prepare power (1.1 Power Ready!!) and cooling (1.2 Cooling Ready!!) in advance.
  4. Process flow:
    • Job allocation from workload scheduling to GPU cluster
    • GPUs request and receive power
    • Temperature rises due to operations
    • Cooling system detects temperature and activates cooling

This diagram illustrates the interconnected workflow in AI data centers, beginning with workload scheduling that enables predictive resource management. The process flows from deterministic power requirements to statistical cooling needs, with the “Prophet Commander” enabling proactive preparation of power and cooling resources. This integrated approach demonstrates how workload prediction can drive efficient resource allocation throughout the entire AI data center ecosystem.

With Claude

Workload trigger

Posted on by lechuck park

From Claude with some prompting
The image appears to be a diagram illustrating a “Workload Trigger” process. It shows three main stages of work:

  1. “Everytime Work”: This stage indicates work that is performed at a regular interval, represented by the repeating gear symbols.
  2. “1 Data Detect Work”: This stage shows data detection work that triggers alerts based on certain conditions, represented by the alert symbols.
  3. “M-Data Analyzed Detect Work”: This stage shows data analysis work that also triggers alerts based on the analysis results, represented by the analyzed detection symbols.

The overall flow of the diagram moves from left to right, with the work cycling through the three main stages. The timing of the work cycles is indicated by the clocks at the start and end of each stage.

The diagram seems to be illustrating some kind of automated monitoring or analysis workflow that triggers alerts based on the detection of certain data patterns or conditions.