Smulyanski: GPU throughput drops sharply at low concurrency due to kernel overheads
Misha Smulyanski · Multi-GPU Kernels, Intelligence per Watt, Heterogeneous Inference, and More | YC Paper Club · Y Combinator · Jul 29, 2026 · at 59:40
Misha Smulyanski explains hardware bottlenecks in low-latency LLM inference architectures during a YC Paper Club presentation.
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“The moment that you start basically going to lower concurrency because you want better interactivity and better latency, Right? The performance the throughput drops. And it drops very sharply because all of a sudden you have a lot of, like, smaller kernels, you have a lot of overheads, you know, you're bound, you're, you know, your memory bandwidths, you're bound by memory bandwidths, and also memory bandwidths is not utilized very well because of all this overheads.”
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