Refactoring of QR: stabilized Gram-Schmidt for split=1 and TS-QR for split=0

benchmarks/cb/linalg.py

@@ -16,14 +16,12 @@ def matmul_split_1(a, b):
 
 @monitor()
 def qr_split_0(a):
-    for t in range(2, 3):
-        qr = a.qr(tiles_per_proc=t)
+    qr = ht.linalg.qr(a)
 
 
 @monitor()
 def qr_split_1(a):
-    for t in range(1, 3):
-        qr = a.qr(tiles_per_proc=t)
+    qr = ht.linalg.qr(a)
 
 
 @monitor()
@@ -53,12 +51,16 @@ def run_linalg_benchmarks():
     matmul_split_1(a, b)
     del a, b
 
+    n = int((4000000 // MPI.COMM_WORLD.size) ** 0.5)
+    m = MPI.COMM_WORLD.size * n
+    a_0 = ht.random.random((m, n), split=0)
+    qr_split_0(a_0)
+    del a_0
+
     n = 2000
-    a_0 = ht.random.random((n, n), split=0)
     a_1 = ht.random.random((n, n), split=1)
-    qr_split_0(a_0)
     qr_split_1(a_1)
-    del a_0, a_1
+    del a_1
 
     n = 50
     A = ht.random.random((n, n), dtype=ht.float64, split=0)