The Microsecond Lie: Why your Go timers are lying about the GPU
The article discusses the inaccuracies of CPU timers when measuring GPU performance in Go programming. It highlights the importance of using CUDA Events for precise timing, revealing that initial measurements were misleading. The author emphasizes the need for accurate metrics to optimize AI infrastructure effectively.
- ▪CPU timers can misrepresent GPU performance by only measuring the time taken to enqueue tasks, not the actual computation time.
- ▪Using CUDA Events provides a more accurate measurement by recording timestamps directly from the GPU.
- ▪The author found that the actual compute time was significantly longer than what CPU timers indicated, leading to potential performance miscalculations.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3395918) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Eitamos Ring Posted on May 23 The Microsecond Lie: Why your Go timers are lying about the GPU #ai #programming #go #cuda TL;DR: I thought my CUDA kernel was running in 160 microseconds. I was wrong. Here is how I used CUDA Events in pure Go to find the real hardware time, and why CPU-side timers are the wrong tool for GPU forensics. I wrapped my kernel launch in a standard Go time.Since(start) block and saw 162 microseconds. I thought I had built a speed demon.
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