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distributed -> remote (#82)

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Robert Nishihara
2016-06-03 18:41:45 -07:00
committed by Philipp Moritz
parent 67086f663e
commit 2b52b91acb
10 changed files with 86 additions and 86 deletions
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lib/python/arrays/dist/linalg.py
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+8 -8
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@@ -8,7 +8,7 @@ from core import *
__all__ = ["tsqr", "modified_lu", "tsqr_hr", "qr"]
@halo.distributed([DistArray], [DistArray, np.ndarray])
@halo.remote([DistArray], [DistArray, np.ndarray])
def tsqr(a):
"""
arguments:
@@ -80,7 +80,7 @@ def tsqr(a):
return q_result, r
# TODO(rkn): This is unoptimized, we really want a block version of this.
@halo.distributed([DistArray], [DistArray, np.ndarray, np.ndarray])
@halo.remote([DistArray], [DistArray, np.ndarray, np.ndarray])
def modified_lu(q):
"""
Algorithm 5 from http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-175.pdf
@@ -110,19 +110,19 @@ def modified_lu(q):
U = np.triu(q_work)[:b, :]
return numpy_to_dist(halo.push(L)), U, S # TODO(rkn): get rid of push and pull
@halo.distributed([np.ndarray, np.ndarray, np.ndarray, int], [np.ndarray, np.ndarray])
@halo.remote([np.ndarray, np.ndarray, np.ndarray, int], [np.ndarray, np.ndarray])
def tsqr_hr_helper1(u, s, y_top_block, b):
y_top = y_top_block[:b, :b]
s_full = np.diag(s)
t = -1 * np.dot(u, np.dot(s_full, np.linalg.inv(y_top).T))
return t, y_top
@halo.distributed([np.ndarray, np.ndarray], [np.ndarray])
@halo.remote([np.ndarray, np.ndarray], [np.ndarray])
def tsqr_hr_helper2(s, r_temp):
s_full = np.diag(s)
return np.dot(s_full, r_temp)
@halo.distributed([DistArray], [DistArray, np.ndarray, np.ndarray, np.ndarray])
@halo.remote([DistArray], [DistArray, np.ndarray, np.ndarray, np.ndarray])
def tsqr_hr(a):
"""Algorithm 6 from http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-175.pdf"""
q, r_temp = tsqr(a)
@@ -132,15 +132,15 @@ def tsqr_hr(a):
r = tsqr_hr_helper2(s, r_temp)
return y, t, y_top, r
@halo.distributed([np.ndarray, np.ndarray, np.ndarray, np.ndarray], [np.ndarray])
@halo.remote([np.ndarray, np.ndarray, np.ndarray, np.ndarray], [np.ndarray])
def qr_helper1(a_rc, y_ri, t, W_c):
return a_rc - np.dot(y_ri, np.dot(t.T, W_c))
@halo.distributed([np.ndarray, np.ndarray], [np.ndarray])
@halo.remote([np.ndarray, np.ndarray], [np.ndarray])
def qr_helper2(y_ri, a_rc):
return np.dot(y_ri.T, a_rc)
@halo.distributed([DistArray], [DistArray, DistArray])
@halo.remote([DistArray], [DistArray, DistArray])
def qr(a):
"""Algorithm 7 from http://www.eecs.berkeley.edu/Pubs/TechRpts/2013/EECS-2013-175.pdf"""
m, n = a.shape[0], a.shape[1]