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Replace use of queue mgr #1735

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Merged
antonwolfy merged 10 commits into from
Mar 20, 2024
+72 −327
Merged

Replace use of queue mgr #1735

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6db800d
Remove use of deprecated DPCTLQueueMgr_* functions
oleksandr-pavlyk Mar 1, 2024
b578f87
Removed setting DPNP_LOCAL_QUEUE in tests
oleksandr-pavlyk Mar 1, 2024
6309f26
Removed uses of device_context
oleksandr-pavlyk Mar 1, 2024
67867d8
Removed trailing whitespace
oleksandr-pavlyk Mar 17, 2024
c11b779
Replaced tab with spaces
oleksandr-pavlyk Mar 17, 2024
814ad56
Use backend_sycl_singleton, remove backend_sycl
oleksandr-pavlyk Mar 18, 2024
bf24b22
Removed pre-preprocessor fenced out dead code
oleksandr-pavlyk Mar 19, 2024
ac1b43a
Formatting suggested by pre-commit hooks
oleksandr-pavlyk Mar 19, 2024
d479168
Merge branch 'master' into replace-use-of-queue-mgr
antonwolfy Mar 19, 2024
f9b1db7
Addressed issues raised by @diptorupd
oleksandr-pavlyk Mar 19, 2024
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Removed uses of device_context
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@oleksandr-pavlyk
oleksandr-pavlyk committed Mar 17, 2024
commit 6309f2694322475f6b7d67f53ba4da601e5cffa0
23 changes: 13 additions & 10 deletions doc/dpctl.rst
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Expand Up @@ -10,20 +10,23 @@ Interplay with the Data Parallel Control Library
An example below demonstrates how the Data Parallel Extension for NumPy* can be
easily combined with the device management interface provided by dpctl package.

Literally, the SYCL* queue manager interface from the dpctl package allows
to set an input queue as the currently usable queue inside the context
manager's scope. This way an array creation function from the dpnp package
which is defined inside the context will allocate the data using that queue.

.. code-block:: python
:linenos:

import dpctl
import dpnp as np
import dpctl
import dpnp

d = dpctl.select_cpu_device()
x = dpnp.array([1, 2, 3], device=d)
s = dpnp.sum(x)

y = dpnp.linspace(0, dpnp.pi, num=10**6, device="gpu")
f = 1 + y * dpnp.sin(y)

with dpctl.device_context("opencl:gpu"):
x = np.array([1, 2, 3])
s = np.sum(x)
# locate argument where function attains global maximum
max_arg = x[dpnp.argmax(f)]
max_val = dpnp.max(f)


For more information please refer to `Data Parallel Control Library`_
documentation.
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11 changes: 3 additions & 8 deletions examples/example10.py
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Expand Up @@ -87,12 +87,7 @@ def example():


if __name__ == "__main__":
try:
import dpctl
import dpctl

with dpctl.device_context("opencl:gpu") as gpu_queue:
gpu_queue.get_sycl_device().print_device_info()
example()

except ImportError:
example()
dpctl.select_default_device().print_device_info()
example()
7 changes: 1 addition & 6 deletions tests/third_party/intel/zero-copy-test1.py
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Expand Up @@ -62,12 +62,7 @@ def dppy_f(array_like_obj):
hb = np.arange(0, global_size, dtype="i4")
da = DuckUSMArray(hb.shape, dtype=hb.dtype, host_buffer=hb)

if dpctl.has_gpu_queues(dpctl.backend_type.level_zero):
print("\nScheduling on OpenCL GPU\n")
with dpctl.device_context("opencl:gpu") as gpu_queue:
dppy_f[global_size, dppy.DEFAULT_LOCAL_SIZE](da)
else:
print("\nSkip scheduling on OpenCL GPU\n")
dppy_f[global_size, dppy.DEFAULT_LOCAL_SIZE](da)

assert da[0] == 10

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