我有一个 OpenCL 程序，它可以很好地解决小问题，但是当运行较大的问题时，在 Nvidia 硬件上运行内核的时间超过了 8-10 秒。虽然我没有连接到我正在计算的 GPU（Nvidia GTX580）上的显示器，但内核在运行大约 8-10 秒后总是会终止。
我对这个问题所做的初步研究表明，只有当显示器连接到显卡时，Nvidia 看门狗才应该强制执行时间限制。但是，我没有任何显示器连接到 OpenCl 正在运行的 GPU，但仍然强制执行此限制。
是否可以禁用 Nvidia 看门狗或让驱动程序识别 Mac OS X 10.7.4 中的 GTX580 没有连接显示器？
我知道解决这个问题的一种可能方法是分解成更小的内核，但是由于我的工作性质，当我使用更细的颗粒时，我仍然可以达到这个限制。
我正在编译/运行的系统如下：
- MacPro4,1 2 x 2.26 GHz 四核 Intel Xeon
- Mac OS X 10.7.4
- XCode 4.3.3
- Nvidia GT120（已连接 2 个显示器）
- NVidia GTX580（无附件）
有关运行 NVidia 设备查询时的额外信息，我会得到以下输出：
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!