Sergey Pokhodenko

SDC testing CI does not work in CentOS 7 docker container It was hard to indicate the problem via debugger just tried Ubuntu image. It is because there are new...

Revise initialization part of the HPAT and load required libraries on demand (not all of them at startup)

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_Originally posted by @shssf in https://github.com/IntelPython/hpat/pull/253#pullrequestreview-307293162

Default value for `skipna` should be `None` or `True` when implementing methods in new style

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> Are you sure that `skipna=None` here? It is better to refer to Pandas sources. We had am examples before where we found a bug in Pandas documentation _Originally posted...

According to [Numba docs](http://numba.pydata.org/numba-doc/latest/extending/high-level.html#implementing-functions) `@overload...` functions should return nothing (None) if it can not return function for given input types. All our current implementations of attributes, methods and functions in...

Correct way to document implementations of methods in new style

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Actually `axis` could be a string (`'index'` or `'columns'`), not only an integer. You could add string type here. Moreover you could check on typing stage of the implementation that...

- parfor nodes in @jit functions - check with additional issues, like dpnp library calls

Move examples outside of numba_dpex to root folder

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I am not sure that examples should be a part of the package. We could install if but it is mostly for developers (not users) and easiest way to work...

Support for `@guvectorize` is missing. Features: - [ ] Passing intra-device arrays - [ ] Launch asynchronous - [ ] Calling Device Functions - [ ] Explicitly control the maximum...

`@reduce` decorator

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We currently do not have anything similar to `@cuda.reduce` and the output of this step should be a design to support a similar `@reduce` decorator for `numba-dppy`. Features to implement:...

Support for Calling Device Functions from Ufuncs

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dpex ufunc kernels cannot be called from other dpex device functions. Example: ```python @dppy.func def a_device_function(a): return a + 1 @vectorize(nopython=True) def ufunc_kernel(x, y): return a_device_function(x) + y def test_ufunc():...