time_1 = time.clock() NufftObj = NUFFT_hsa() time_2 = time.clock() # mem_usage = memory_usage((NufftObj.plan,(om, Nd, Kd, Jd))) # print(mem_usage) NufftObj.plan(om, Nd, Kd, Jd) time_3 = time.clock() # NufftObj.offload('cuda') # for GPU computation NufftObj.offload('ocl') # for multi-CPU computation time_4 = time.clock() dtype = np.complex64 time_5 = time.clock() print("send image to device") NufftObj.x_Nd = NufftObj.thr.to_device(image.astype(dtype)) print("copy image to gx") time_6 = time.clock() gx = NufftObj.thr.copy_array(NufftObj.x_Nd) time_7 = time.clock() print('total:', time_7 - time_1, '/Decl obj: ', time_2 - time_1, '/plan: ', \ time_3 - time_2, '/offload: ', time_4 - time_3, '/to_device: ', time_6 - time_5, '\copy_array: ', time_7 - time_6) else: NufftObj = NUFFT_cpu() # mem_usage = memory_usage((NufftObj.plan,(om, Nd, Kd, Jd))) # print(mem_usage) NufftObj.plan(om, Nd, Kd, Jd) # Compute F_hat if gpu == True: time_comp = time.clock()
def test_init(): # cm = matplotlib.cm.gray # load example image import pkg_resources DATA_PATH = pkg_resources.resource_filename('pynufft', 'src/data/') # PHANTOM_FILE = pkg_resources.resource_filename('pynufft', 'data/phantom_256_256.txt') import numpy # import matplotlib.pyplot import scipy image = scipy.misc.ascent()[::2,::2] image=image.astype(numpy.float)/numpy.max(image[...]) Nd = (256, 256) # image space size Kd = (512, 512) # k-space size Jd = (6,6) # interpolation size # load k-space points om = numpy.load(DATA_PATH+'om2D.npz')['arr_0'] nfft = NUFFT_cpu() # CPU nfft.plan(om, Nd, Kd, Jd) try: NufftObj = NUFFT_hsa('cuda',0,0) except: NufftObj = NUFFT_hsa('ocl',0,0) # NufftObj2 = NUFFT_hsa('cuda',0,0) NufftObj.debug = 1 NufftObj.plan(om, Nd, Kd, Jd, radix=2) # NufftObj2.plan(om, Nd, Kd, Jd) # NufftObj.offload(API = 'cuda', platform_number = 0, device_number = 0) # NufftObj2.offload(API = 'cuda', platform_number = 0, device_number = 0) # NufftObj2.offload('cuda') # NufftObj.offload(API = 'cuda', platform_number = 0, device_number = 0) # print('api=', NufftObj.thr.api_name()) # NufftObj.offload(API = 'ocl', platform_number = 0, device_number = 0) y = nfft.k2y(nfft.xx2k(nfft.x2xx(image))) NufftObj.x_Nd = NufftObj.thr.to_device( image.astype(dtype)) gx = NufftObj.thr.copy_array(NufftObj.x_Nd) print('x close? = ', numpy.allclose(image, gx.get() , atol=1e-4)) gxx = NufftObj.x2xx(gx) print('xx close? = ', numpy.allclose(nfft.x2xx(image), gxx.get() , atol=1e-4)) gk = NufftObj.xx2k(gxx) k = nfft.xx2k(nfft.x2xx(image)) print('k close? = ', numpy.allclose(nfft.xx2k(nfft.x2xx(image)), gk.get(), atol=1e-3*numpy.linalg.norm(k))) gy = NufftObj.k2y(gk) k2 = NufftObj.y2k(gy) print('y close? = ', numpy.allclose(y, gy.get() , atol=1e-3*numpy.linalg.norm(y)), numpy.linalg.norm((y - gy.get())/numpy.linalg.norm(y))) y2 = y print('k2 close? = ', numpy.allclose(nfft.y2k(y2), k2.get(), atol=1e-3*numpy.linalg.norm(nfft.y2k(y2)) ), numpy.linalg.norm(( nfft.y2k(y2)- k2.get())/numpy.linalg.norm(nfft.y2k(y2)))) gxx2 = NufftObj.k2xx(k2) # print('xx close? = ', numpy.allclose(nfft.k2xx(nfft.y2k(y2)), NufftObj.xx_Nd.get(queue=NufftObj.queue, async=False) , atol=0.1)) gx2 = NufftObj.xx2x(gxx2) print('x close? = ', numpy.allclose(nfft.adjoint(y2), gx2.get() , atol=1e-3*numpy.linalg.norm(nfft.adjoint(y2)))) image3 = gx2.get() import time t0 = time.time() # k = nfft.xx2k(nfft.x2xx(image)) for pp in range(0,50): # y = nfft.k2y(nfft.xx2k(nfft.x2xx(image))) y = nfft.forward(image) # y = nfft.k2y(k) # k = nfft.y2k(y) # x = nfft.adjoint(y) # y = nfft.forward(image) # y2 = NufftObj.y.get( NufftObj.queue, async=False) t_cpu = (time.time() - t0)/50.0 print(t_cpu) # del nfft gy2=NufftObj.forward(gx) # gk = NufftObj.xx2k(NufftObj.x2xx(gx)) t0= time.time() for pp in range(0,20): # pass gy2 = NufftObj.forward(gx) # gy2 = NufftObj.k2y(gk) # gx2 = NufftObj.adjoint(gy2) # gk2 = NufftObj.y2k(gy2) # del gy2 # c = gx2.get() # gy=NufftObj.forward(gx) NufftObj.thr.synchronize() t_cl = (time.time() - t0)/20 print(t_cl) print('gy close? = ', numpy.allclose(y, gy.get(), atol=numpy.linalg.norm(y)*1e-3)) print("acceleration=", t_cpu/t_cl) maxiter =100 import time t0= time.time() # x2 = nfft.solve(y2, 'cg',maxiter=maxiter) x2 = nfft.solve(y2, 'L1TVOLS',maxiter=maxiter, rho = 2) t1 = time.time()-t0 # gy=NufftObj.thr.copy_array(NufftObj.thr.to_device(y2)) t0= time.time() # x = NufftObj.solve(gy,'cg', maxiter=maxiter) x = NufftObj.solve(gy,'L1TVOLS', maxiter=maxiter, rho=2) t2 = time.time() - t0 print(t1, t2) print('acceleration=', t1/t2 ) # k = x.get() # x = nfft.k2xx(k)/nfft.st['sn'] # return try: import matplotlib.pyplot matplotlib.pyplot.subplot(1, 2, 1) matplotlib.pyplot.imshow( x.get().real, cmap= matplotlib.cm.gray, vmin = 0, vmax = 1) matplotlib.pyplot.title("HSA reconstruction") matplotlib.pyplot.subplot(1, 2,2) matplotlib.pyplot.imshow(x2.real, cmap= matplotlib.cm.gray) matplotlib.pyplot.title("CPU reconstruction") matplotlib.pyplot.show(block = False) matplotlib.pyplot.pause(3) matplotlib.pyplot.close() # del NufftObj.thr # del NufftObj except: print("no graphics")