Hi,
Are there particular reasons to build Amber14 with a specific cuda version
among 5.0, 5.5, and 6.0 ? (aside from newer is better)
When is Amber support for cuda 6.5 expected ?
The target machine has
+------------------------------------------------------+
| NVIDIA-SMI 331.62 Driver Version: 331.62 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Tesla M2070 On | 0000:11:00.0 Off | 0 |
| N/A N/A P0 N/A / N/A | 672MiB / 5375MiB | 83% E. Thread |
+-------------------------------+----------------------+----------------------+
| 1 Tesla M2070 On | 0000:14:00.0 Off | 0 |
| N/A N/A P0 N/A / N/A | 621MiB / 5375MiB | 87% E. Thread |
+-------------------------------+----------------------+----------------------+
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 2 CUDA Capable device(s)
Device 0: "Tesla M2070"
CUDA Driver Version / Runtime Version 6.0 / 5.0
CUDA Capability Major/Minor version number: 2.0
Total amount of global memory: 5375 MBytes (5636554752 bytes)
(14) Multiprocessors x ( 32) CUDA Cores/MP: 448 CUDA Cores
GPU Clock rate: 1147 MHz (1.15 GHz)
Memory Clock rate: 1566 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 kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device PCI Bus ID / PCI location ID: 20 / 0
Compute Mode:
< Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device) >
thanks,
scott
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Received on Tue Sep 02 2014 - 13:00:08 PDT
