Skip to contentSkip to filters

We use cookies for analytics.

Scaling Agentic Inference Across Heterogeneous Compute

About

Zain Asgar examines running agent inference across heterogeneous hardware. The discussion covers splitting workloads between GPUs and CPUs, compilation for different targets, automated kernel optimisation and hardware-aware scheduling. It also explores networking constraints and trade-offs among numerical precision, application accuracy, performance and cost.

Topics

agent inferenceheterogeneous hardwareGPUsCPUscompilationautomated kernel optimisationhardware-aware schedulingnetworking constraintsnumerical precision

Related episodes

More from The TWIML AI Podcast

All episodes

More with Sam Charrington

All their work

New episodes in Artificial Intelligence

All episodes