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.
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| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/eitamos_ring_0508146ca448/the-microsecond-lie-why-your-go-timers-are-lying-about-the-gpu-2gp5 |
| Publication time | Sat, 23 May 2026 19:12:52 +0000 |
| Retrieval time | 2026-05-23T19:37:27.624Z |
| Last seen | 2026-05-23T19:37:27.624Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | kP1IFTVtlok9 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
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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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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