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5min chapter
Heterogeneous Computing with Raja Koduri
Oxide and Friends
Exploring Memory Intensive Workloads and GPU Efficiency
Explore the significance of memory in LLM workloads, comparing GPU architectures like Nvidia, AMD, and Intel using transport analogies. The discussion highlights the challenges of achieving performance across hardware variations due to implicit biases in data and compute packing.
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Discover
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Listen to the best highlights from the podcasts you love and dive into the full episode