我有一个OpenCL程序可以很好地解决小问题，但是当运行较大的问题超过8-10s在Nvidia硬件上运行内核的时间限制。虽然我没有连接到GPU上的监视器（Nvidia GTX580），但内核在运行大约8-10秒后总会被终止。
我对此问题所做的初步研究表明，如果显示器连接到显卡，Nvidia看门狗应该只执行时间限制。但是我没有连接到运行OpenCl的GPU的监视器，但仍然强制执行此限制。
是否可以禁用Nvidia监视程序或让驱动程序识别Mac OS X 10.7.4中没有监视器连接到GTX580？
我知道可能解决这个问题的方法是分解成较小的内核，但是由于我工作的性质，当我更精细的时候，我仍然可以达到这个极限。
我正在编译/运行的系统如下：
有关运行NVidia设备查询的额外信息，我得到以下输出：
CUDA Device Query (Runtime API) version (CUDART static linking)
Found 2 CUDA Capable device(s)
Device 0: "GeForce GTX 580"
CUDA Driver Version / Runtime Version 4.2 / 4.2
CUDA Capability Major/Minor version number: 2.0
Total amount of global memory: 1536 MBytes (1610285056 bytes)
(16) Multiprocessors x ( 32) CUDA Cores/MP: 512 CUDA Cores
GPU Clock rate: 1564 MHz (1.56 GHz)
Memory Clock rate: 2004 Mhz
Memory Bus Width: 384-bit
L2 Cache Size: 786432 bytes
Max Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536,65535), 3D=(2048,2048,2048)
Max Layered Texture Size (dim) x layers 1D=(16384) x 2048, 2D=(16384,16384) x 2048
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 32768
Warp size: 32
Maximum number of threads per multiprocessor: 1536
Maximum number of threads per block: 1024
Maximum sizes of each dimension of a block: 1024 x 1024 x 64
Maximum sizes of each dimension of a grid: 65535 x 65535 x 65535
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Concurrent kernel execution: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support enabled: No
Device is using TCC driver mode: No
Device supports Unified Addressing (UVA): Yes
Device PCI Bus ID / PCI location ID: 6 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 1: "GeForce GT 120"
CUDA Driver Version / Runtime Version 4.2 / 4.2
CUDA Capability Major/Minor version number: 1.1
Total amount of global memory: 512 MBytes (536543232 bytes)
( 4) Multiprocessors x ( 8) CUDA Cores/MP: 32 CUDA Cores
GPU Clock rate: 1400 MHz (1.40 GHz)
Memory Clock rate: 800 Mhz
Memory Bus Width: 128-bit
Max Texture Dimension Size (x,y,z) 1D=(8192), 2D=(65536,32768), 3D=(2048,2048,2048)
Max Layered Texture Size (dim) x layers 1D=(8192) x 512, 2D=(8192,8192) x 512
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 16384 bytes
Total number of registers available per block: 8192
Warp size: 32
Maximum number of threads per multiprocessor: 768
Maximum number of threads per block: 512
Maximum sizes of each dimension of a block: 512 x 512 x 64
Maximum sizes of each dimension of a grid: 65535 x 65535 x 1
Maximum memory pitch: 2147483647 bytes
Texture alignment: 256 bytes
Concurrent copy and execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Concurrent kernel execution: No
Alignment requirement for Surfaces: Yes
Device has ECC support enabled: No
Device is using TCC driver mode: No
Device supports Unified Addressing (UVA): No
Device PCI Bus ID / PCI location ID: 5 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 4.2, CUDA Runtime Version = 4.2, NumDevs = 2, Device = GeForce GTX 580, Device = GeForce GT 120
[deviceQuery] test results...
PASSED
> exiting in 3 seconds: 3...2...1...done!
答案 0 :(得分：0)
我前段时间一直在寻找这个问题的答案......我从来没有找到解决方案。
但这无论如何都不应该“解决” 如果用户只有一个GPU，你会怎么做？让用户PC只需冻结10秒以上？这将是一个有趣的软件... ...
我将它拆分为多个子内核，或者如果你的内核中有一个循环，你也可以为每个内核执行一次迭代。只需将当前迭代器值保存到缓冲区，然后在下次执行时从该点重新启动。
这应该适用于您的应用程序，因为它似乎不像某种游戏那样的实时应用程序。