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<title>NVIDIA CUDA Library: cudaThreadSetLimit</title>
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<div class="navpath"><a class="el" href="group__CUDART__THREAD__DEPRECATED.html">Thread Management [DEPRECATED]</a>
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<a class="anchor" name="gd636fe22576028cdf3d2c271b544b316"></a><!-- doxytag: member="cuda_runtime_api.h::cudaThreadSetLimit" ref="gd636fe22576028cdf3d2c271b544b316" args="(enum cudaLimit limit, size_t value)" -->
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<td class="memname"><a class="el" href="group__CUDART__TYPES_gf599e5b8b829ce7db0f5216928f6ecb6.html#gf599e5b8b829ce7db0f5216928f6ecb6">cudaError_t</a> cudaThreadSetLimit </td>
<td>(</td>
<td class="paramtype">enum <a class="el" href="group__CUDART__TYPES_g4c4b34c054d383b0e9a63ab0ffc93651.html#g4c4b34c054d383b0e9a63ab0ffc93651">cudaLimit</a> </td>
<td class="paramname"> <em>limit</em>, </td>
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<td class="paramtype">size_t </td>
<td class="paramname"> <em>value</em></td><td> </td>
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<p>
<dl compact><dt><b><a class="el" href="deprecated.html#_deprecated000003">Deprecated:</a></b></dt><dd></dd></dl>
Note that this function is deprecated because its name does not reflect its behavior. Its functionality is identical to the non-deprecated function <a class="el" href="group__CUDART__DEVICE_gb8a22e29cc297634b0702db0b69f59e7.html#gb8a22e29cc297634b0702db0b69f59e7" title="Set resource limits.">cudaDeviceSetLimit()</a>, which should be used instead.<p>
Setting <code>limit</code> to <code>value</code> is a request by the application to update the current limit maintained by the device. The driver is free to modify the requested value to meet h/w requirements (this could be clamping to minimum or maximum values, rounding up to nearest element size, etc). The application can use <a class="el" href="group__CUDART__THREAD__DEPRECATED_gfd87d16d2bbf4bc41a892f3f75bac5e0.html#gfd87d16d2bbf4bc41a892f3f75bac5e0" title="Returns resource limits.">cudaThreadGetLimit()</a> to find out exactly what the limit has been set to.<p>
Setting each <a class="el" href="group__CUDART__TYPES_g4c4b34c054d383b0e9a63ab0ffc93651.html#g4c4b34c054d383b0e9a63ab0ffc93651">cudaLimit</a> has its own specific restrictions, so each is discussed here.<p>
<ul>
<li><a class="el" href="group__CUDART__TYPES_g4c4b34c054d383b0e9a63ab0ffc93651.html#gg4c4b34c054d383b0e9a63ab0ffc93651fc8f54e641c9b133f1b57703d22ce656">cudaLimitStackSize</a> controls the stack size of each GPU thread. This limit is only applicable to devices of compute capability 2.0 and higher. Attempting to set this limit on devices of compute capability less than 2.0 will result in the error <a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e0038c3b950b6f8668f7282fae25bfcefd13a">cudaErrorUnsupportedLimit</a> being returned.</li></ul>
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<ul>
<li><a class="el" href="group__CUDART__TYPES_g4c4b34c054d383b0e9a63ab0ffc93651.html#gg4c4b34c054d383b0e9a63ab0ffc9365123b80a6221a6853e918c2816bb76742c">cudaLimitPrintfFifoSize</a> controls the size of the shared FIFO used by the printf() and fprintf() device system calls. Setting <a class="el" href="group__CUDART__TYPES_g4c4b34c054d383b0e9a63ab0ffc93651.html#gg4c4b34c054d383b0e9a63ab0ffc9365123b80a6221a6853e918c2816bb76742c">cudaLimitPrintfFifoSize</a> must be performed before launching any kernel that uses the printf() or fprintf() device system calls, otherwise <a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e00383e8aef5398ee38e28ed41e357b48917c">cudaErrorInvalidValue</a> will be returned. This limit is only applicable to devices of compute capability 2.0 and higher. Attempting to set this limit on devices of compute capability less than 2.0 will result in the error <a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e0038c3b950b6f8668f7282fae25bfcefd13a">cudaErrorUnsupportedLimit</a> being returned.</li></ul>
<p>
<ul>
<li><a class="el" href="group__CUDART__TYPES_g4c4b34c054d383b0e9a63ab0ffc93651.html#gg4c4b34c054d383b0e9a63ab0ffc93651b399716bf0a592bc42055473c1273881">cudaLimitMallocHeapSize</a> controls the size of the heap used by the malloc() and free() device system calls. Setting <a class="el" href="group__CUDART__TYPES_g4c4b34c054d383b0e9a63ab0ffc93651.html#gg4c4b34c054d383b0e9a63ab0ffc93651b399716bf0a592bc42055473c1273881">cudaLimitMallocHeapSize</a> must be performed before launching any kernel that uses the malloc() or free() device system calls, otherwise <a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e00383e8aef5398ee38e28ed41e357b48917c">cudaErrorInvalidValue</a> will be returned. This limit is only applicable to devices of compute capability 2.0 and higher. Attempting to set this limit on devices of compute capability less than 2.0 will result in the error <a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e0038c3b950b6f8668f7282fae25bfcefd13a">cudaErrorUnsupportedLimit</a> being returned.</li></ul>
<p>
<dl compact><dt><b>Parameters:</b></dt><dd>
<table border="0" cellspacing="2" cellpadding="0">
<tr><td valign="top"></td><td valign="top"><em>limit</em> </td><td>- Limit to set </td></tr>
<tr><td valign="top"></td><td valign="top"><em>value</em> </td><td>- Size in bytes of limit</td></tr>
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</dl>
<dl class="return" compact><dt><b>Returns:</b></dt><dd><a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e0038e355f04607d824883b4a50662830d591">cudaSuccess</a>, <a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e0038c3b950b6f8668f7282fae25bfcefd13a">cudaErrorUnsupportedLimit</a>, <a class="el" href="group__CUDART__TYPES_g3f51e3575c2178246db0a94a430e0038.html#gg3f51e3575c2178246db0a94a430e00383e8aef5398ee38e28ed41e357b48917c">cudaErrorInvalidValue</a> </dd></dl>
<dl class="note" compact><dt><b>Note:</b></dt><dd>Note that this function may also return error codes from previous, asynchronous launches.</dd></dl>
<dl class="see" compact><dt><b>See also:</b></dt><dd><a class="el" href="group__CUDART__DEVICE_gb8a22e29cc297634b0702db0b69f59e7.html#gb8a22e29cc297634b0702db0b69f59e7" title="Set resource limits.">cudaDeviceSetLimit</a> </dd></dl>
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