Unverified50% confidenceCautionExact time
In ragged prefill scenarios, GPU-CPU synchronization operations disrupt the overlap between computation and scheduling and introduce latency jitter.
1
Sources
50%
Confidence
Long-term
Relevance
9/7/2026
First Seen
Sources
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Related Claims
UnverifiedEliminating redundant synchronization in the TRT-LLM ragged prefill path allows the GPU to maintain a more continuous computation flow, achieving higher throughput and more stable latency in variable-length input batching scenarios.77% similarUnverifiedGPU显存无法超卖，显存溢出会导致OOM直接崩溃，这与CPU的时间片复用有本质区别75% similarUnverifiedSynchronization operations between GPU and CPU (such as cudaStreamSynchronize) force the CPU to wait for the GPU to complete all current tasks, thereby interrupting the asynchronous execution pipeline.74% similarUnverifiedCPU+GPU hybrid inference uses a layer-level offloading mechanism, controlling the number of offloaded layers via the n_gpu_layers parameter; the main bottleneck is PCIe bandwidth latency, which typically reduces generation speed to 1/3 to 1/2 of pure GPU inference.71% similarUnverified间接绘制允许将DrawCall参数存储在GPU缓冲区中，CPU只需发起一次vkCmdDrawIndirectCount调用，配合描述符堆使渲染循环的CPU参与度趋近于零68% similar
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