1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
|
# import our rule system interface
import NvRules
def get_identifier():
# an internal identifier used to map rules to a section, whitespace is not allowed
return "TemplateRule1"
def get_name():
# a descriptive, user-readable name for the rule, e.g. 'Memory Utilization Analysis'
return "Basic Template Rule"
def get_description():
# an optional description for the rule, e.g. 'Analyze memory unit utilization for this kernel'
return "A rule template, demonstration basic NvRules functionality"
def get_section_identifier():
# an internal identifier used to map rules to a section, whitespace is not allowed
return "RuleTemplateSection"
# the main function for a rule, the 'handle' parameter is used to retrieve the rule context
def apply(handle):
# get the rule context, which provides all remaining functions, access to actions, metrics etc.
ctx = NvRules.get_context(handle)
# select the first action (CUDA kernel) from the first range (CUDA stream)
action = ctx.range_by_idx(0).action_by_idx(0)
# get the frontend object, which interacts with the UI and profiler report
fe = ctx.frontend()
# get two metrics from this action
grid_size = int(action.metric_by_name("launch__grid_size").as_double())
block_size = int(action.metric_by_name("launch__block_size").as_double())
# post a message to the frontend
fe.message("Kernel " + action.name() + " launch config: " + str(grid_size) + "x" + str(block_size))
# post a warning message to the frontend
fe.message(NvRules.IFrontend.MsgType_MSG_WARNING, "This is what a warning of the analysis might look like")
# load a couple of charts and tables which are defined in small file snippets
fe.load_chart_from_file("RuleTemplate_bar.chart")
fe.load_chart_from_file("RuleTemplate_table.chart")
|
