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* Add type annotations for future functionality
```python
class Timer:
def start(self) -> None: ...
def stop(self) -> None: ...
```
and overloaded `State.exec` so:
- normal mode accepts `Callable[[Launch], None]`
- `timer=True` accepts `Callable[[Launch, Timer], None]`
No implementation yet. Type annotation checked with
```
(py313) :~/repos/nvbench/python$ python -m mypy --ignore-missing-imports /tmp/check_timer.py
/tmp/check_timer.py:24: error: No overload variant of "exec" of "State" matches argument types "Callable[[Launch], None]", "bool" [call-overload]
/tmp/check_timer.py:24: note: Possible overload variants:
/tmp/check_timer.py:24: note: def exec(self, Callable[[Launch], None], /, *, batched: bool | None = ..., sync: bool | None = ..., timer: Literal[False] = ...) -> None
/tmp/check_timer.py:24: note: def exec(self, Callable[[Launch, Timer], None], /, *, timer: Literal[True], sync: bool | None = ...) -> None
/tmp/check_timer.py:25: error: Argument 1 to "exec" of "State" has incompatible type "Callable[[Launch, Timer], None]"; expected "Callable[[Launch], None]" [arg-type]
/tmp/check_timer.py:26: error: No overload variant of "exec" of "State" matches argument types "Callable[[Launch, int], None]", "bool" [call-overload]
/tmp/check_timer.py:26: note: Possible overload variants:
/tmp/check_timer.py:26: note: def exec(self, Callable[[Launch], None], /, *, batched: bool | None = ..., sync: bool | None = ..., timer: Literal[False] = ...) -> None
/tmp/check_timer.py:26: note: def exec(self, Callable[[Launch, Timer], None], /, *, timer: Literal[True], sync: bool | None = ...) -> None
Found 3 errors in 1 file (checked 1 source file)
(py313) :~/repos/nvbench/python$ nl -ba /tmp/check_timer.py
1 # /tmp/check_nvbench_timer.py
2 import cuda.bench as bench
3
4 def normal_ok(launch: bench.Launch) -> None:
5 pass
6
7 def timer_ok(launch: bench.Launch, timer: bench.Timer) -> None:
8 timer.start()
9 timer.stop()
10
11 def missing_timer(launch: bench.Launch) -> None:
12 pass
13
14 def extra_timer(launch: bench.Launch, timer: bench.Timer) -> None:
15 pass
16
17 def wrong_timer_type(launch: bench.Launch, timer: int) -> None:
18 pass
19
20 def state_bench(state: bench.State) -> None:
21 state.exec(normal_ok)
22 state.exec(normal_ok, timer=False)
23 state.exec(timer_ok, timer=True)
24 state.exec(missing_timer, timer=True) # should fail
25 state.exec(extra_timer) # should fail
26 state.exec(wrong_timer_type, timer=True) # should fail
```
* Implement cuda.bench.Timer object
The Timer class is not user-constructible. It exposes two nullary
methods timer.start() and timer.stop().
The instance of Timer class would be provided to launchable object
passed to State.exec with timer=True.
* Implement support for State.exec( launch_fn, timer=True)
* Change type annotation for batch to default to None
None is interpreted as `not timer`, i.e., it effectively
defaults to True (as before) for usage without timer set,
but starts defaulting to `False` is `timer=True` is set.
The batched keyword type is `bool | None`.
* Implement default batched=None behavior
API allows one to specify all 3 keywords, sync, batched,
and timer. batched is None by default, run-time interpreted
as `(not timer)`.
* Update tests for new behavior of batched/time combination
* Add python/examples/exec_tag_timer.py
* Expand Timer class and methods docstrings
* Reworked python/example/exec_tag_timer.py to align with C++ example.
* Replace ::cuda::std::name with cuda::std::name
* Resolve review feedback
89 lines
2.7 KiB
Python
89 lines
2.7 KiB
Python
# Copyright 2025-2026 NVIDIA Corporation
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#
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# Licensed under the Apache License, Version 2.0 with the LLVM exception
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# (the "License"); you may not use this file except in compliance with
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# the License.
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#
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# You may obtain a copy of the License at
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#
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# http://llvm.org/foundation/relicensing/LICENSE.txt
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import sys
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import cuda.bench as bench
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import cuda.cccl.headers as headers
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import cuda.core as core
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def as_core_Stream(cs: bench.CudaStream) -> core.Stream:
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"Create view into native stream provided by NVBench"
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return core.Stream.from_handle(cs.addressof())
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def make_sleep_kernel():
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"""JITs sleep_kernel(seconds)"""
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src = r"""
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#include <cuda/std/cstdint>
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#include <cuda/std/chrono>
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// Each launched thread just sleeps for `seconds`.
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__global__ void sleep_kernel(double seconds) {
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namespace chrono = cuda::std::chrono;
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using hr_clock = chrono::high_resolution_clock;
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auto duration = static_cast<cuda::std::int64_t>(seconds * 1e9);
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const auto ns = chrono::nanoseconds(duration);
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const auto start = hr_clock::now();
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const auto finish = start + ns;
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auto now = hr_clock::now();
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while (now < finish)
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{
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now = hr_clock::now();
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}
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}
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"""
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incl = headers.get_include_paths()
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opts = core.ProgramOptions(include_path=str(incl.libcudacxx))
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prog = core.Program(src, code_type="c++", options=opts)
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mod = prog.compile("cubin", name_expressions=("sleep_kernel",))
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return mod.get_kernel("sleep_kernel")
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@bench.register()
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@bench.axis.float64("Duration", [1e-4 + k * 0.25e-3 for k in range(5)])
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@bench.axis.string("Kramble", ["Foo", "Bar", "Baz"])
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def runtime_skip(state: bench.State):
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duration = state.get_float64("Duration")
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kramble = state.get_string("Kramble")
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# Skip Baz benchmarks with 0.8 ms duration
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if kramble == "Baz" and duration < 0.8e-3:
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state.skip("Short 'Baz' benchmarks are skipped")
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return
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# Skip Foo benchmark with > 0.3 ms duration
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if kramble == "Foo" and duration > 0.3e-3:
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state.skip("Long 'Foo' benchmarks are skipped")
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return
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krn = make_sleep_kernel()
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launch_cfg = core.LaunchConfig(grid=1, block=1, shmem_size=0)
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def launcher(launch: bench.Launch):
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s = as_core_Stream(launch.get_stream())
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core.launch(s, launch_cfg, krn, duration)
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state.exec(launcher)
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if __name__ == "__main__":
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bench.run_all_benchmarks(sys.argv)
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