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import ctypes, ctypes.util
import os
# If this is failing, make sure that the directory containing libsmctrl.so is
# in your LD_LIBRARY_PATH environment variable. You likely need something like:
# LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/playpen/jbakita/gpu_subdiv/libsmctrl/
libsmctrl_path = ctypes.util.find_library("libsmctrl")
if not libsmctrl_path:
libsmctrl_path = __path__[0] + "/../libsmctrl.so"
libsmctrl = ctypes.CDLL(libsmctrl_path)
def get_gpc_info(device_num):
"""
Obtain list of thread processing clusters (TPCs) enabled for each general
processing cluster (GPC) in the specified GPU.
Parameters
----------
device_num : int
Which device to obtain information for (starts as 0, order is defined
by nvdebug module). May not match CUDA device numbering.
Returns
-------
list of int64
A list as long as the number of GPCs enabled, where each list entry is
a bitmask. A bit set at index `i` indicates that TPC `i` is part of the
GPC at that list index. Obtained via GPU register reads in `nvdebug`.
"""
num_gpcs = ctypes.c_uint()
tpc_masks = ctypes.pointer(ctypes.c_ulonglong())
res = libsmctrl.libsmctrl_get_gpc_info(ctypes.byref(num_gpcs), ctypes.byref(tpc_masks), device_num)
if res != 0:
print("pysmctrl: Unable to call libsmctrl_get_gpc_info(). Raising error %d..."%res)
raise OSError(res, os.strerror(res))
return [tpc_masks[i] for i in range(num_gpcs.value)]
def get_tpc_info(device_num):
"""
Obtain a count of the total number of thread processing clusters (TPCs)
enabled on the specified GPU.
Parameters
----------
device_num : int
Which device to obtain TPC count for (starts as 0, order is defined by
`nvdebug` module). May not match CUDA device numbering.
Returns
-------
int
Count of enabled TPCs. Obtained via GPU register reads in `nvdebug`.
"""
num_tpcs = ctypes.c_uint()
res = libsmctrl.libsmctrl_get_tpc_info(ctypes.byref(num_tpcs), device_num)
if res != 0:
print("pysmctrl: Unable to call libsmctrl_get_tpc_info(). Raising error %d..."%res)
raise OSError(res, os.strerror(res))
return num_tpcs.value
def get_tpc_info_cuda(device_num):
"""
Obtain a count of the total number of thread processing clusters (TPCs)
enabled on the specified GPU.
Parameters
----------
device_num : int
Which device to obtain TPC count for, as a CUDA device ID.
Returns
-------
int
Count of enabled TPCs. Obtained via calculations on data from CUDA.
"""
num_tpcs = ctypes.c_uint()
res = libsmctrl.libsmctrl_get_tpc_info_cuda(ctypes.byref(num_tpcs), device_num)
if res != 0:
print("pysmctrl: Unable to call libsmctrl_get_tpc_info_cuda(). Raising error %d..."%res)
raise OSError(res, os.strerror(res))
return num_tpcs.value
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