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Re-write MPISimulator.py with hip-python

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Hicham Agueny 2024-02-26 10:45:49 +01:00
parent e188c8ea03
commit 655913021c
1 changed files with 47 additions and 10 deletions
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GPUSimulators/MPISimulator.py
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@ -26,9 +26,9 @@ import numpy as np
from mpi4py import MPI from mpi4py import MPI
import time import time
import pycuda.driver as cuda #import pycuda.driver as cuda
#import nvtx #import nvtx
from hip import hip, hiprtc
class MPIGrid(object): class MPIGrid(object):
@ -292,16 +292,53 @@ class MPISimulator(Simulator.BaseSimulator):
#Note that east and west also transfer ghost cells #Note that east and west also transfer ghost cells
#whilst north/south only transfer internal cells #whilst north/south only transfer internal cells
#Reuses the width/height defined in the read-extets above #Reuses the width/height defined in the read-extets above
self.in_e = cuda.pagelocked_empty((int(self.nvars), int(self.read_e[3]), int(self.read_e[2])), dtype=np.float32) #np.empty((self.nvars, self.read_e[3], self.read_e[2]), dtype=np.float32) ##self.in_e = cuda.pagelocked_empty((int(self.nvars), int(self.read_e[3]), int(self.read_e[2])), dtype=np.float32) #np.empty((self.nvars, self.read_e[3], self.read_e[2]), dtype=np.float32)
self.in_w = cuda.pagelocked_empty((int(self.nvars), int(self.read_w[3]), int(self.read_w[2])), dtype=np.float32) #np.empty((self.nvars, self.read_w[3], self.read_w[2]), dtype=np.float32)
self.in_n = cuda.pagelocked_empty((int(self.nvars), int(self.read_n[3]), int(self.read_n[2])), dtype=np.float32) #np.empty((self.nvars, self.read_n[3], self.read_n[2]), dtype=np.float32) ##self.in_w = cuda.pagelocked_empty((int(self.nvars), int(self.read_w[3]), int(self.read_w[2])), dtype=np.float32) #np.empty((self.nvars, self.read_w[3], self.read_w[2]), dtype=np.float32)
self.in_s = cuda.pagelocked_empty((int(self.nvars), int(self.read_s[3]), int(self.read_s[2])), dtype=np.float32) #np.empty((self.nvars, self.read_s[3], self.read_s[2]), dtype=np.float32) ##self.in_n = cuda.pagelocked_empty((int(self.nvars), int(self.read_n[3]), int(self.read_n[2])), dtype=np.float32) #np.empty((self.nvars, self.read_n[3], self.read_n[2]), dtype=np.float32)
##self.in_s = cuda.pagelocked_empty((int(self.nvars), int(self.read_s[3]), int(self.read_s[2])), dtype=np.float32) #np.empty((self.nvars, self.read_s[3], self.read_s[2]), dtype=np.float32)
self.in_e = np.empty((int(self.nvars), int(self.read_e[3]), int(self.read_e[2])), dtype=np.float32)
num_bytes_e = self.in_e.size * self.in_e.itemsize
#hipHostMalloc allocates pinned host memory which is mapped into the address space of all GPUs in the system, the memory can be accessed directly by the GPU device
#hipHostMallocDefault:Memory is mapped and portable (default allocation)
#hipHostMallocPortable: memory is explicitely portable across different devices
self.in_e = hip_check(hip.hipHostMalloc(num_bytes_e,hip.hipHostMallocPortable))
self.in_w = np.empty((int(self.nvars), int(self.read_w[3]), int(self.read_w[2])), dtype=np.float32)
num_bytes_w = self.in_w.size * self.in_w.itemsize
self.in_w = hip_check(hip.hipHostMalloc(num_bytes_w,hip.hipHostMallocPortable))
self.in_n = np.empty((int(self.nvars), int(self.read_n[3]), int(self.read_n[2])), dtype=np.float32)
num_bytes_n = self.in_n.size * self.in_n.itemsize
self.in_n = hip_check(hip.hipHostMalloc(num_bytes_n,hip.hipHostMallocPortable))
self.in_s = np.empty((int(self.nvars), int(self.read_s[3]), int(self.read_s[2])), dtype=np.float32)
num_bytes_s = self.in_s.size * self.in_s.itemsize
self.in_s = hip_check(hip.hipHostMalloc(num_bytes_s,hip.hipHostMallocPortable))
#Allocate data for sending #Allocate data for sending
self.out_e = cuda.pagelocked_empty((int(self.nvars), int(self.read_e[3]), int(self.read_e[2])), dtype=np.float32) #np.empty_like(self.in_e) #self.out_e = cuda.pagelocked_empty((int(self.nvars), int(self.read_e[3]), int(self.read_e[2])), dtype=np.float32) #np.empty_like(self.in_e)
self.out_w = cuda.pagelocked_empty((int(self.nvars), int(self.read_w[3]), int(self.read_w[2])), dtype=np.float32) #np.empty_like(self.in_w) #self.out_w = cuda.pagelocked_empty((int(self.nvars), int(self.read_w[3]), int(self.read_w[2])), dtype=np.float32) #np.empty_like(self.in_w)
self.out_n = cuda.pagelocked_empty((int(self.nvars), int(self.read_n[3]), int(self.read_n[2])), dtype=np.float32) #np.empty_like(self.in_n) #self.out_n = cuda.pagelocked_empty((int(self.nvars), int(self.read_n[3]), int(self.read_n[2])), dtype=np.float32) #np.empty_like(self.in_n)
self.out_s = cuda.pagelocked_empty((int(self.nvars), int(self.read_s[3]), int(self.read_s[2])), dtype=np.float32) #np.empty_like(self.in_s) #self.out_s = cuda.pagelocked_empty((int(self.nvars), int(self.read_s[3]), int(self.read_s[2])), dtype=np.float32) #np.empty_like(self.in_s)
self.out_e = np.empty((int(self.nvars), int(self.read_e[3]), int(self.read_e[2])), dtype=np.float32)
num_bytes_e = self.out_e.size * self.out_e.itemsize
self.out_e = hip_check(hip.hipHostMalloc(num_bytes_e,hip.hipHostMallocPortable))
self.out_w = np.empty((int(self.nvars), int(self.read_w[3]), int(self.read_w[2])), dtype=np.float32)
num_bytes_w = self.out_w.size * self.out_w.itemsize
self.out_w = hip_check(hip.hipHostMalloc(num_bytes_w,hip.hipHostMallocPortable))
self.out_n = np.empty((int(self.nvars), int(self.read_n[3]), int(self.read_n[2])), dtype=np.float32)
num_bytes_n = self.out_n.size * self.out_n.itemsize
self.out_n = hip_check(hip.hipHostMalloc(num_bytes_n,hip.hipHostMallocPortable))
self.out_s = np.empty((int(self.nvars), int(self.read_s[3]), int(self.read_s[2])), dtype=np.float32)
num_bytes_s = self.out_s.size * self.out_s.itemsize
self.out_s = hip_check(hip.hipHostMalloc(num_bytes_s,hip.hipHostMallocPortable))
self.logger.debug("Simlator rank {:d} initialized on {:s}".format(self.grid.comm.rank, MPI.Get_processor_name())) self.logger.debug("Simlator rank {:d} initialized on {:s}".format(self.grid.comm.rank, MPI.Get_processor_name()))