In the current landscape of the technology world, Graphics Processing Units (GPUs) have become the most valuable infrastructure assets. However, it is not just a matter of having these chips, but rather their optimal management. Experts believe that GPUs sitting idle in data centers are exactly like commercial airplanes grounded in hangars; both impose exorbitant maintenance and depreciation costs on their owners instead of generating wealth.
For leading companies in the field of artificial intelligence, every second of downtime for a processing cluster means lost training opportunities and billions in costs. Optimizing resource allocation and preventing the waste of processing power has now become one of the key strategies for successful businesses in this field to ensure their return on investment amidst the intense competition of the AI market.