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General attribute-based heterogeneity support with hard and soft constraints (#248)

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* attribute-based heterogeneity-awareness in global scheduler and photon

* minor post-rebase fix

* photon: enforce dynamic capacity constraint on task dispatch

* globalsched: cap the number of times we try to schedule a task in round robin

* propagating ability to specify resource capacity to ray.init

* adding resources to remote function export and fetch/register

* globalsched: remove unused functions; update cached photon resource capacity (until next photon heartbeat)

* Add some integration tests.

* globalsched: cleanup + factor out constraint checking

* lots of style

* task_spec_required_resource: global refactor

* clang format

* clang format + comment update in photon

* clang format photon comment

* valgrind

* reduce verbosity for Travis

* Add test for scheduler load balancing.

* addressing comments

* refactoring global scheduler algorithm

* Minor cleanups.

* Linting.

* Fix array_test.py and linting.

* valgrind fix for photon tests

* Attempt to fix stress tests.

* fix hashmap free

* fix hashmap free comment

* memset photon resource vectors to 0 in case they get used before the first heartbeat

* More whitespace changes.

* Undo whitespace error I introduced.
This commit is contained in:
Alexey Tumanov
2017-02-09 01:34:14 -08:00
committed by Robert Nishihara
parent 1a7e1c47cb
commit dfb6107b22
22 changed files with 1037 additions and 226 deletions
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test/array_test.py
+1 -1
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@@ -66,7 +66,7 @@ class DistributedArrayTest(unittest.TestCase):
def testMethods(self):
for module in [ra.core, ra.random, ra.linalg, da.core, da.random, da.linalg]:
reload(module)
ray.worker._init(start_ray_local=True, num_workers=10, num_local_schedulers=2)
ray.worker._init(start_ray_local=True, num_workers=10, num_local_schedulers=2, num_cpus=[10, 10])
x = da.zeros.remote([9, 25, 51], "float")
assert_equal(ray.get(da.assemble.remote(x)), np.zeros([9, 25, 51]))