In 30 seconds
Rene Haas argues that CPUs remain important alongside AI accelerators and discusses orchestration around training and inference. The specific division of work depends on system design.
- 1A system componentHaas expects CPUs to remain part of computing systems.
- 2Changing workloadsTraining and inference require broader system support.
- 3CoordinationHardware and software share orchestration and routing work.
Takeaways
- AI accelerators operate within larger systems.
- CPUs can support control and coordination.
- The division of work varies by architecture.
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CPUs and accelerators
Arm CEO Rene Haas argues that CPUs remain important in computing systems even as specialized AI accelerators become more prominent.
Arm CEO Rene Haas argues that CPUs remain important in computing systems even as specialized AI accelerators become more prominent.
He describes CPUs as a component of overall system design rather than treating an accelerator as the entire system.
System orchestration
Haas discusses workloads including training, reinforcement learning and inference, and says the surrounding infrastructure must coordinate data and execution.
Haas discusses workloads including training, reinforcement learning and inference, and says the surrounding infrastructure must coordinate data and execution.
He uses a transport analogy for orchestration and routing. The precise division of work varies by hardware and software architecture.
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