Cold-Cache Serving Without GPU Warmup
Traditional serving runtimes require a dedicated warmup phase prior to processing user requests to prime GPU execution caches and allocators, incurring substantial startup delay on consumer edge devices. By contrast, cold-cache serving eliminates pre-warming entirely by construction. The engine begins serving the first incoming request immediately with an unpopulated, cold GPU expert cache. Initial expert requests naturally trigger cache misses that are processed directly by the standard decode miss path through concurrent PCIe cache fills and in-place CPU execution. As generation proceeds, the expert cache warms organically during ordinary inference without requiring synthetic warmup passes.
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Prep Sessions
Edge-Native Mixture-of-Experts Serving with FreeToken @ University of Michigan - Ann Arbor
Ch.3 Adaptive Runtime Policies and Device Execution - Edge-Native Mixture-of-Experts Serving with FreeToken @ University of Michigan - Ann Arbor
Elastic Runtime Cache Reconfiguration and Fast Bootstrap - Edge-Native Mixture-of-Experts Serving with FreeToken @ University of Michigan - Ann Arbor
Related
Dynamic VRAM Availability and Memory Split Shifts in Edge MoE Serving
Runtime Cache Reconfiguration at Scheduler Safe Points
Recurring Engine Bootstrap Bottleneck in Edge MoE Serving
Direct Host Layout Loading with Deferred Memory Pinning
Cold-Cache Serving Without GPU Warmup
Match each environment or operational phase in MoE serving to its corresponding operational characteristic.
Loading a 140 GB expert pool from a 7 GB/s NVMe drive takes roughly ___ seconds prior to any GPU warmup.
Order the events that occur when an MoE serving engine is initialized on an edge device to evaluate an inference request.
Analyze the operational trade-offs of Policy A versus Policy B with respect to system memory availability and user-visible latency on this edge workstation.
Which two operations must be completed during Mixture-of-Experts (MoE) serving engine initialization before the first request can be evaluated?
Why do users on personal edge devices frequently terminate the MoE serving engine after running inference?
Evaluate the architectural implications of engine initialization overhead across edge and datacenter environments. Contrast how operational lifespans in these two environments determine whether startup latency is successfully amortized or manifests as a recurring, user-visible bottleneck.
Direct Host Layout Loading with Deferred Memory Pinning
Cold-Cache Serving Without GPU Warmup
Learn After
How does the GPU expert cache transition to a warm state in a cold-cache serving runtime?
In traditional serving runtimes, a dedicated warmup phase is used prior to processing user requests in order to prime GPU execution caches and allocators.
What major performance penalty do traditional serving runtimes impose on consumer edge devices by requiring a dedicated GPU warmup phase?
Describe how a cold-cache serving engine handles initial expert requests when starting with an unpopulated GPU cache, detailing the specific execution and transfer mechanisms used.