MPI中复杂乘法的Python代码不一致性
假设有一个Python MPI程序,其中主节点向每个工作节点发送一对复杂矩阵,工作节点应该计算它们的乘积(传统的矩阵乘积)。输入矩阵在主节点根据某种算法构造,无需解释。现在,为了简单起见,假设我们只有两个MPI进程,一个主进程和一个工作进程。我已经为这个案例创建了两个版本的程序。第一种方法构造两个复数(为了简单起见,是1乘1矩阵),并将它们发送给工作人员以计算乘积。这个程序就像一个骨架,我正试图与多个工人做什么。在第二个程序中,我省略了算法,只是将这两个复数硬编码到代码中。这些程序应提供与此处所示相同的产品:MPI中复杂乘法的Python代码不一致性,python,numpy,mpi,complex-numbers,mpi4py,Python,Numpy,Mpi,Complex Numbers,Mpi4py,假设有一个Python MPI程序,其中主节点向每个工作节点发送一对复杂矩阵,工作节点应该计算它们的乘积(传统的矩阵乘积)。输入矩阵在主节点根据某种算法构造,无需解释。现在,为了简单起见,假设我们只有两个MPI进程,一个主进程和一个工作进程。我已经为这个案例创建了两个版本的程序。第一种方法构造两个复数(为了简单起见,是1乘1矩阵),并将它们发送给工作人员以计算乘积。这个程序就像一个骨架,我正试图与多个工人做什么。在第二个程序中,我省略了算法,只是将这两个复数硬编码到代码中。这些程序应提供与此处所
a=28534314.10478439+28534314.10478436j
b=-1.398115e+09+1.398115e+09j
a*b=-7.97922802e+16+48j
这已经在Matlab中进行了检查。相反,第一个程序不工作,工人给出a*b=-7.97922801e+16+28534416.j
,而第二个程序正常工作。请注意,在这两种情况下,数据都正确地从主机传输到工作机(请参阅print()
函数)。第一个(错误的)程序是:
from mpi4py import MPI
import numpy as np
N = 1
ell = 9
s_cod = 7
var = np.array([np.exp(1j*2*np.pi*1/8)])
comm = MPI.COMM_WORLD
if comm.rank == 0:
print("I am sender")
#Construction algorithm, explanation skipped
A=np.matrix('1 0; 0 1')
B=np.matrix('1 0; 0 1')
Ah=np.split(A,2)
Bh=np.split(B,2)
Ahv = []
Bhv = []
for i in range(2):
Ahv.append(np.split(Ah[i], 2, axis=1))
Bhv.append(np.split(Bh[i], 2, axis=1))
a = []
b = []
for i in range(N):
a.append(Ahv[0][0]*(pow(s_cod*var[i], ell)) + Ahv[1][0] + Ahv[0][1]*(pow(s_cod*var[i], ell+1)) + Ahv[1][1]*s_cod*var[i])
b.append(Bhv[0][0] + Bhv[1][0]*(pow(s_cod*var[i], ell)) + Bhv[0][1]*(pow(s_cod*var[i], 2)) + Bhv[1][1]*(pow(s_cod*var[i], ell+2)))
#Send message with a predefined tag, like 15 and 16, to each receiver
for i in range(N):
comm.Isend([a[i],MPI.COMPLEX], dest=i+1, tag=15)
comm.Isend([b[i],MPI.COMPLEX], dest=i+1, tag=16)
print("Sender sent: ")
print(a[0])
print(b[0])
else:
print("I am receiver")
A = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
B = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
#Receive message with tags 15, 16 from rank 0
rA = comm.Irecv(A, source=0, tag=15)
rB = comm.Irecv(B, source=0, tag=16)
rA.wait()
rB.wait()
C = np.dot(A, B)
print("Receiver received: ")
print(A)
print(B)
print("Receiver computed: ")
print(C)
from mpi4py import MPI
import numpy as np
comm = MPI.COMM_WORLD
if comm.rank == 0:
print("I am sender")
a = np.matrix('28534314.10478439+28534314.10478436j')
b = np.matrix('-1.39818115e+09+1.39818115e+09j')
#Send message with a predefined tag, like 15 and 16, to rank 1
comm.Isend([a, MPI.COMPLEX], dest=1, tag=15)
comm.Isend([b, MPI.COMPLEX], dest=1, tag=16)
print("Sender sent: ")
print(a[0])
print(b[0])
else:
print("I am receiver")
A = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
B = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
#Receive message with tags 15, 16 from rank 0
rA = comm.Irecv(A, source=0, tag=15)
rB = comm.Irecv(B, source=0, tag=16)
rA.wait()
rB.wait()
C = np.dot(A, B)
print("Receiver received: ")
print(A)
print(B)
print("Receiver computed: ")
print(C)
第二个(正确的)程序是:
from mpi4py import MPI
import numpy as np
N = 1
ell = 9
s_cod = 7
var = np.array([np.exp(1j*2*np.pi*1/8)])
comm = MPI.COMM_WORLD
if comm.rank == 0:
print("I am sender")
#Construction algorithm, explanation skipped
A=np.matrix('1 0; 0 1')
B=np.matrix('1 0; 0 1')
Ah=np.split(A,2)
Bh=np.split(B,2)
Ahv = []
Bhv = []
for i in range(2):
Ahv.append(np.split(Ah[i], 2, axis=1))
Bhv.append(np.split(Bh[i], 2, axis=1))
a = []
b = []
for i in range(N):
a.append(Ahv[0][0]*(pow(s_cod*var[i], ell)) + Ahv[1][0] + Ahv[0][1]*(pow(s_cod*var[i], ell+1)) + Ahv[1][1]*s_cod*var[i])
b.append(Bhv[0][0] + Bhv[1][0]*(pow(s_cod*var[i], ell)) + Bhv[0][1]*(pow(s_cod*var[i], 2)) + Bhv[1][1]*(pow(s_cod*var[i], ell+2)))
#Send message with a predefined tag, like 15 and 16, to each receiver
for i in range(N):
comm.Isend([a[i],MPI.COMPLEX], dest=i+1, tag=15)
comm.Isend([b[i],MPI.COMPLEX], dest=i+1, tag=16)
print("Sender sent: ")
print(a[0])
print(b[0])
else:
print("I am receiver")
A = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
B = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
#Receive message with tags 15, 16 from rank 0
rA = comm.Irecv(A, source=0, tag=15)
rB = comm.Irecv(B, source=0, tag=16)
rA.wait()
rB.wait()
C = np.dot(A, B)
print("Receiver received: ")
print(A)
print(B)
print("Receiver computed: ")
print(C)
from mpi4py import MPI
import numpy as np
comm = MPI.COMM_WORLD
if comm.rank == 0:
print("I am sender")
a = np.matrix('28534314.10478439+28534314.10478436j')
b = np.matrix('-1.39818115e+09+1.39818115e+09j')
#Send message with a predefined tag, like 15 and 16, to rank 1
comm.Isend([a, MPI.COMPLEX], dest=1, tag=15)
comm.Isend([b, MPI.COMPLEX], dest=1, tag=16)
print("Sender sent: ")
print(a[0])
print(b[0])
else:
print("I am receiver")
A = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
B = np.empty_like(np.matrix([[0]*(1) for i in range(1)])).astype(np.complex128)
#Receive message with tags 15, 16 from rank 0
rA = comm.Irecv(A, source=0, tag=15)
rB = comm.Irecv(B, source=0, tag=16)
rA.wait()
rB.wait()
C = np.dot(A, B)
print("Receiver received: ")
print(A)
print(B)
print("Receiver computed: ")
print(C)
我正在使用mpi4py3.0.0。以及Python 2.7.14和OpenMPI 2.1.2的内核。我已经为这个问题纠结了一整天,仍然不知道发生了什么。我尝试过许多初始化,如
np.zeros()
,np.zeros_-like()
,np.empty_-like()
,以及np.array
和np.matrix
和函数np.dot()
,np.matmul()
和操作符*/code>。最后,根据我尝试过的其他例子,我认为问题总是与产品的虚部有关。有什么建议吗?这与MPI完全无关
np.set_printoptions(precision=15)
确认计算的a
和b
实际上与您输入到“正确”版本的不同
我不确定结果的基本真相是什么。在计算过程中,可能会出现影响增大的舍入误差。在点积过程中,差异急剧显现,因为在“正确”版本中,b
的实部/虚部的绝对值相等,而在计算版本中,它们仅相对接近,但存在显著的绝对差异