starpupy: apply two-dimension Numpy matrix

starpupy/examples/starpu_py_parallel.py

@@ -196,8 +196,11 @@ print("the program execution time is", end_exec5-start_exec5)
 print("the cpu execution time is", end_cpu5-start_cpu5)
 
 print("--(multi_2arr)(A, B)")
-A=np.arange(N)
-B=np.arange(N, 2*N, 1)
+# A=np.arange(N)
+# B=np.arange(N, 2*N, 1)
+n, m = 4, 5
+A = np.arange(n*m).reshape(n, m)
+B = np.arange(n*m, 2*n*m, 1).reshape(n, m)
 print("The input arrays are A", A, "B", B)
 start_exec6=time.time()
 start_cpu6=time.process_time()

starpupy/src/joblib.py

@@ -53,6 +53,26 @@ def partition(ls, n_block):
 		L=[ls[i:i+1] for i in range (len(ls))]
 	return L
 
+# split a two-dimension numpy matrix into n_block numbers of sub-matrices
+def array2d_split(a, n_block):
+	# decompose number of n_jobs to two integers multiply
+	c_tmp=math.floor(math.sqrt(n_block))
+	for i in range (c_tmp,0,-1):
+		if n_block%i==0:
+			c=i
+			r=int(n_block/c)
+			break
+	# split column
+	arr_split_c=np.array_split(a,c,0)
+	arr_split=[]
+	# split row
+	for i in range(c):
+		arr_split_r=np.array_split(arr_split_c[i],r,1)
+		for j in range(r):
+			arr_split.append(arr_split_r[j])
+	return arr_split
+
+
 def future_generator(iterable, n_jobs, dict_task):
 	# iterable is generated by delayed function, after converting to a list, the format is [function, (arg1, arg2, ... ,)]
 	#print("iterable type is ", type(iterable))
@@ -91,10 +111,16 @@ def future_generator(iterable, n_jobs, dict_task):
 			args_split.append([])
 			# if the array is an numpy array
 			if type(args[i]) is np.ndarray:
-				# split numpy array
-				args_split[i]=np.array_split(args[i],n_block)
-				# get the length of numpy array
-				l_arr.append(args[i].size)
+				# one-dimension matrix
+				if args[i].ndim==1:
+					# split numpy array
+					args_split[i]=np.array_split(args[i],n_block)
+					# get the length of numpy array
+					l_arr.append(args[i].size)
+				# two-dimension matrix
+				elif args[i].ndim==2:
+					# split numpy 2D array
+					args_split[i]=array2d_split(args[i],n_block)
 			# if the array is a generator
 			elif isinstance(args[i],types.GeneratorType):
 				# split generator