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Use cuda.Stream.from_handle to create core.Stream from nvbench.CudaStream

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This commit is contained in:
Oleksandr Pavlyk
2025-07-02 15:09:12 -05:00
parent b357af0092
commit 883e5819b6
4 changed files with 34 additions and 49 deletions
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12
python/examples/auto_throughput.py
View File

@@ -63,13 +63,9 @@ def throughput_bench(state: nvbench.State):
state.exec(launcher)
(
nvbench.register(throughput_bench)
.addInt64Axis("Stride", [1, 4])
.addInt64Axis("ItemsPerThread", [1, 2, 3, 4])
)
if __name__ == "__main__":
print(nvbench.__version__)
b = nvbench.register(throughput_bench)
b.addInt64Axis("Stride", [1, 2, 4])
b.addInt64Axis("ItemsPerThread", [1, 2, 3, 4])
nvbench.run_all_benchmarks(sys.argv)

44
python/examples/axes.py
View File

@@ -7,6 +7,10 @@ import cuda.core.experimental as core
import cuda.nvbench as nvbench
def as_core_Stream(cs: nvbench.CudaStream) -> core.Stream:
return core.Stream.from_handle(cs.addressof())
def make_sleep_kernel():
"""JITs sleep_kernel(seconds)"""
src = r"""
@@ -45,10 +49,7 @@ def simple(state: nvbench.State):
launch_config = core.LaunchConfig(grid=1, block=1, shmem_size=0)
def launcher(launch: nvbench.Launch):
dev = core.Device()
dev.set_current()
s = dev.create_stream(launch.getStream())
s = as_core_Stream(launch.getStream())
core.launch(s, launch_config, krn, sleep_dur)
state.exec(launcher)
@@ -61,10 +62,7 @@ def single_float64_axis(state: nvbench.State):
launch_config = core.LaunchConfig(grid=1, block=1, shmem_size=0)
def launcher(launch: nvbench.Launch):
dev = core.Device()
dev.set_current()
s = dev.create_stream(launch.getStream())
s = as_core_Stream(launch.getStream())
core.launch(s, launch_config, krn, sleep_dur)
state.exec(launcher)
@@ -117,21 +115,16 @@ def copy_sweep_grid_shape(state: nvbench.State):
state.addGlobalMemoryReads(nbytes)
state.addGlobalMemoryWrites(nbytes)
dev = core.Device(state.getDevice())
dev.set_current()
alloc_stream = dev.create_stream(state.getStream())
input_buf = core.DeviceMemoryResource(dev.device_id).allocate(nbytes, alloc_stream)
output_buf = core.DeviceMemoryResource(dev.device_id).allocate(nbytes, alloc_stream)
dev_id = state.getDevice()
alloc_s = as_core_Stream(state.getStream())
input_buf = core.DeviceMemoryResource(dev_id).allocate(nbytes, alloc_s)
output_buf = core.DeviceMemoryResource(dev_id).allocate(nbytes, alloc_s)
krn = make_copy_kernel()
launch_config = core.LaunchConfig(grid=num_blocks, block=block_size, shmem_size=0)
def launcher(launch: nvbench.Launch):
dev = core.Device()
dev.set_current()
s = dev.create_stream(launch.getStream())
s = as_core_Stream(launch.getStream())
core.launch(s, launch_config, krn, input_buf, output_buf, num_values)
state.exec(launcher)
@@ -160,21 +153,16 @@ def copy_type_sweep(state: nvbench.State):
state.addGlobalMemoryReads(nbytes)
state.addGlobalMemoryWrites(nbytes)
dev = core.Device(state.getDevice())
dev.set_current()
alloc_stream = dev.create_stream(state.getStream())
input_buf = core.DeviceMemoryResource(dev.device_id).allocate(nbytes, alloc_stream)
output_buf = core.DeviceMemoryResource(dev.device_id).allocate(nbytes, alloc_stream)
dev_id = state.getDevice()
alloc_s = as_core_Stream(state.getStream())
input_buf = core.DeviceMemoryResource(dev_id).allocate(nbytes, alloc_s)
output_buf = core.DeviceMemoryResource(dev_id).allocate(nbytes, alloc_s)
krn = make_copy_kernel(value_cuda_t, value_cuda_t)
launch_config = core.LaunchConfig(grid=256, block=256, shmem_size=0)
def launcher(launch: nvbench.Launch):
dev = core.Device()
dev.set_current()
s = dev.create_stream(launch.getStream())
s = as_core_Stream(launch.getStream())
core.launch(s, launch_config, krn, input_buf, output_buf, num_values)
state.exec(launcher)

17
python/examples/exec_tag_sync.py
View File

@@ -7,6 +7,11 @@ import cuda.core.experimental as core
import cuda.nvbench as nvbench
def as_core_Stream(cs: nvbench.CudaStream) -> core.Stream:
"Create view of native stream used by NVBench"
return core.Stream.from_handle(cs.addressof())
def make_fill_kernel(data_type: Optional[str] = None):
src = r"""
#include <cuda/std/cstdint>
@@ -40,11 +45,8 @@ def synchronizing_bench(state: nvbench.State):
n_values = 64 * 1024 * 1024
n_bytes = n_values * ctypes.sizeof(ctypes.c_int32(0))
dev = core.Device(state.getDevice())
dev.set_current()
alloc_stream = dev.create_stream(state.getStream())
buffer = core.DeviceMemoryResource(dev).allocate(n_bytes, alloc_stream)
alloc_s = as_core_Stream(state.getStream())
buffer = core.DeviceMemoryResource(state.getDevice()).allocate(n_bytes, alloc_s)
state.addElementCount(n_values, "Items")
state.addGlobalMemoryWrites(n_bytes, "Size")
@@ -53,10 +55,7 @@ def synchronizing_bench(state: nvbench.State):
launch_config = core.LaunchConfig(grid=256, block=256, shmem_size=0)
def launcher(launch: nvbench.Launch):
dev = core.Device()
dev.set_current()
s = dev.create_stream(launch.getStream())
s = as_core_Stream(launch.getStream())
core.launch(s, launch_config, krn, buffer, 0, n_values)
s.sync()

10
python/examples/skip.py
View File

@@ -5,6 +5,11 @@ import cuda.core.experimental as core
import cuda.nvbench as nvbench
def as_core_Stream(cs: nvbench.CudaStream) -> core.Stream:
"Create view into native stream provided by NVBench"
return core.Stream.from_handle(cs.addressof())
def make_sleep_kernel():
"""JITs sleep_kernel(seconds)"""
src = r"""
@@ -54,10 +59,7 @@ def runtime_skip(state: nvbench.State):
launch_cfg = core.LaunchConfig(grid=1, block=1, shmem_size=0)
def launcher(launch: nvbench.Launch):
dev = core.Device()
dev.set_current()
s = dev.create_stream(launch.getStream())
s = as_core_Stream(launch.getStream())
core.launch(s, launch_cfg, krn, duration)
state.exec(launcher)