Use USMHost as underlying buffer for result

[oleksandr-pavlyk]

This should improver transfer timing per GPU optimization guidelines

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[github-actions]

Array API standard conformance tests for dpctl=0.14.1dev0=py310h76be34b_47 ran successfully.
Passed: 33
Failed: 801
Skipped: 280

[oleksandr-pavlyk]

This change results in dramatic speed-up of dpt.asnumpy. For example, before the change:

In [1]: import dpctl.tensor as dpt

In [2]: x = dpt.ones(10**7 + 2, dtype='i2', device='gpu')

In [3]: %time y = dpt.asnumpy(x)
CPU times: user 285 µs, sys: 140 ms, total: 141 ms
Wall time: 100 ms

In [4]: %timeit y = dpt.asnumpy(x)
70.7 ms ± 4.13 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

after:

In [1]: import dpctl.tensor as dpt

In [2]: x = dpt.ones(10**7 + 2, dtype='i2', device='gpu')

In [3]: %time y = dpt.asnumpy(x)
CPU times: user 19.3 ms, sys: 69.4 ms, total: 88.7 ms
Wall time: 69.4 ms

In [4]: %timeit y = dpt.asnumpy(x)
15.9 ms ± 956 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)

Consequentially, it improves performance of __repr__.

[github-actions]

Array API standard conformance tests for dpctl=0.14.1dev0=py310h76be34b_47 ran successfully.
Passed: 33
Failed: 801
Skipped: 280

[github-actions]

View rendered docs @ https://intelpython.github.io/dpctl/pulls/1026/index.html

[coveralls]

Coverage: 82.187% (+0.02%) from 82.172% when pulling b6ff2df on faster-asnumpy into e6da513 on master.

[github-actions]

Array API standard conformance tests for dpctl=0.14.1dev0=py310h76be34b_73 ran successfully.
Passed: 33
Failed: 801
Skipped: 280

[ndgrigorian]

LGTM!

[github-actions]

Deleted rendered PR docs from intelpython.github.com/dpctl, latest should be updated shortly. 🤞

[github-actions]

Array API standard conformance tests for dpctl=0.14.1dev0=py310h76be34b_73 ran successfully.
Passed: 33
Failed: 801
Skipped: 280