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占用率计算器 API

cudaOccupancyMaxPotentialBlockSize

占用率计算器 API 是 CoddyKit 上的免费 CUDA Academy 课时。这是第 3 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 CUDA Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 CUDA Academy 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Stop Guessing Block Size

Instead of hand-tuning, CUDA offers an occupancy API that computes a good block size for your kernel automatically.

The Star Function

One call does the heavy lifting: cudaOccupancyMaxPotentialBlockSize suggests a block size that maximizes occupancy.

cudaOccupancyMaxPotentialBlockSize(&grid, &block, myKernel);

What It Returns

It fills in a suggested block size and the minimum grid size needed to fully occupy the device for your kernel.

It Knows Your Kernel

The API reads your kernels real register and shared memory use, so its suggestion fits that exact kernel, not a generic guess.

Predicting Occupancy

A sibling call reports how many active blocks per SM a config gives, so you can predict occupancy before launching.

cudaOccupancyMaxActiveBlocksPerMultiprocessor(&n, k, 256, 0);

Computing the Percentage

Multiply blocks per SM by warps per block, divide by the SM warp max, and you get the theoretical occupancy percentage.

Dynamic Shared Memory

These calls take a dynamic shared memory argument, so the prediction stays accurate when your kernel sizes shared memory at launch.

Portable Across GPUs

Because it queries the running device, the same code picks good sizes on different GPUs without you hardcoding numbers.

Use It at Startup

Call the occupancy API once during initialization, cache the block size, then reuse it for every launch of that kernel.

A Strong Default

The suggested size is an excellent starting point. You can still benchmark a few neighbors to find the true best for your data.

Why It Beats Magic Numbers

Hardcoded sizes like 256 break when resources change. The API adapts, keeping your kernel near peak occupancy automatically.

Quick Check

Recall what cudaOccupancyMaxPotentialBlockSize gives you.

Recap

You met the occupancy API: it suggests a portable, kernel-aware block size and predicts occupancy before you ever launch. ⚙️

常见问题解答

「占用率计算器 API」课时是免费的吗？

是的 — 「占用率计算器 API」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 CUDA Academy 课程的其余内容，请升级到 CoddyKit PRO。 CUDA Academy 课程共包含 4 节课。

「占用率计算器 API」这节课中我会学到什么？

cudaOccupancyMaxPotentialBlockSize 你通过在浏览器中直接运行的动手代码来练习 CUDA Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 CUDA Academy 需要有经验吗？

无需任何先前经验。CoddyKit 上的 CUDA Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 3 节课，共 4 节。

「占用率计算器 API」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 CUDA Academy 课中编写并运行代码吗？

能。每节 CUDA Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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