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Classroom Contents
All About AI Accelerators - GPU, TPU, Dataflow, Near-Memory, Optical, Neuromorphic & More
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- 1 - Intro
- 2 - What does it mean to make hardware for AI?
- 3 - Why were GPUs so successful?
- 4 - What is "dark silicon"?
- 5 - Beyond GPUs: How can we get even faster AI compute?
- 6 - A look at today's accelerator landscape
- 7 - Systolic Arrays and VLIW
- 8 - Reconfigurable dataflow hardware
- 9 - The failure of Wave Computing
- 10 - What is near-memory compute?
- 11 - Optical and Neuromorphic Computing
- 12 - Hardware as enabler and limiter
- 13 - Everything old is new again
- 14 - Where to go to dive deeper?