Unverified50% confidenceFactExact time
When kernels execute concurrently in multiple streams, simple wall-clock timing includes the execution time of other streams, contaminating the performance data of an individual kernel; the correct approach is to use CUDA events to record timestamps within the target stream.
1
Sources
50%
Confidence
Long-term
Relevance
10/27/2026
First Seen
Sources
Hands-On GPU Kernel Development Environment Setup: CUDA 13 Thresholds and Performance Analysis Pitfalls
redditr/deeplearning10/27/2026
Related Entities
Related Claims
UnverifiedWhen measuring kernel execution time with standard CPU timers, if cudaDeviceSynchronize() is not called or CUDA events are not used, what is measured is often the kernel enqueue time rather than the actual execution time.78% similarUnverifiedCUDA events (cudaEvent_t) provide timing capability: cudaEventRecord inserts a timestamp marker into a stream, and cudaEventElapsedTime computes the GPU time between two events, with a precision of about 0.5 microseconds.75% similarUnverifiedBecause the prefill phase must handle variable-length inputs, it often needs to capture CUDA graphs separately for multiple sequence lengths, further amplifying the recording time.68% similarVerifiedA CUDA stream is an asynchronous execution queue on the GPU; operations in different streams can execute concurrently and are a key mechanism for overlapping computation and data transfer.66% similarUnverifiedCUDA的SIMT执行机制中，每个Warp由32个线程组成，在同一时钟周期执行相同指令66% similar
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