def test_OpenCL_CSR(self):
logger.info("Testing CSR-based algorithm (backward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype, best=True)
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " % (devtype, ids, ocl.platforms[ids[0]], ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
ref = ai.integrate1d(data, self.N, method="splitBBox", unit="2th_deg")
try:
res = ai.integrate1d(data, self.N, method="ocl_csr_%i,%i" % (ids[0], ids[1]), unit="2th_deg")
except (pyFAI.opencl.pyopencl.MemoryError, MemoryError, pyFAI.opencl.pyopencl.RuntimeError, RuntimeError) as error:
logger.warning("Memory error on %s dataset %s: %s%s. Converted into Warning: device may not have enough memory." % (devtype, os.path.basename(ds["img"]), os.linesep, error))
break
else:
r = Rwp(ref, res)
logger.info("OpenCL CSR vs histogram SplitBBox has R= %.3f for dataset %s" % (r, ds))
self.assertTrue(r < 3, "Rwp=%.3f for OpenCL CSR processing of %s" % (r, ds))
del ai, data
gc.collect()
def test_OpenCL_LUT(self):
logger.info("Testing LUT-based algorithm (backward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype, best=True)
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " % (devtype, ids, ocl.platforms[ids[0]], ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
try:
res = ai.xrpd_LUT_OCL(data, 1000, devicetype="all", platformid=ids[0], deviceid=ids[1])
except MemoryError as error:
logger.warning("Memory Error on %s dataset %s: %s%s. Converted into warnining: device may not have enough memory." % (devtype, os.path.basename(ds["img"]), os.linesep, error))
else:
t0 = time.time()
ref = ai.xrpd(data, 1000)
t1 = time.time()
res = ai.xrpd_LUT_OCL(data, 1000, safe=False)
t2 = time.time()
logger.info("For image %15s;\tspeed up is %.3fx;\trate is %.3f Hz" % (os.path.basename(ds["img"]), ((t1 - t0) / (t2 - t1)), 1. / (t2 - t1)))
r = Rwp(ref, res)
self.assertTrue(r < 10, "Rwp=%.3f for OpenCL processing of %s" % (r, ds))
def test_OpenCL(self):
logger.info("Testing histogram-based algorithm (forward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype,
extensions=["cl_khr_int64_base_atomics"])
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " %
(devtype, ids, ocl.platforms[ids[0]],
ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
res = ai.xrpd_OpenCL(data,
self.N,
devicetype="all",
platformid=ids[0],
deviceid=ids[1],
useFp64=True)
ref = ai.integrate1d(data,
self.N,
method="splitBBox",
unit="2th_deg")
r = Rwp(ref, res)
logger.info(
"OpenCL histogram vs histogram SplitBBox has R= %.3f for dataset %s"
% (r, ds))
self.assertTrue(
r < 6,
"Rwp=%.3f for OpenCL histogram processing of %s" % (r, ds))
del ai, data
gc.collect()
def test_OpenCL(self):
logger.info("Testing histogram-based algorithm (forward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype,
extensions=["cl_khr_int64_base_atomics"])
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " %
(devtype, ids, ocl.platforms[ids[0]],
ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
res = ai.xrpd_OpenCL(data,
1000,
devicetype="all",
platformid=ids[0],
deviceid=ids[1],
useFp64=True)
t0 = time.time()
ref = ai.xrpd(data, 1000)
t1 = time.time()
res = ai.xrpd_OpenCL(data, 1000, safe=False)
t2 = time.time()
logger.info(
"For image %15s;\tspeed up is %.3fx;\trate is %.3f Hz" %
(os.path.basename(ds["img"]),
((t1 - t0) / (t2 - t1)), 1. / (t2 - t1)))
r = Rwp(ref, res)
self.assertTrue(
r < 10, "Rwp=%.3f for OpenCL processing of %s" % (r, ds))
def test_correct(self):
test2d = {"numpy": self.eps,
"cython": self.eps,
"splitbbox": self.eps,
"splitpix": self.eps,
"lut": self.eps,
}
if ocl:
for device in ["cpu", "gpu", "acc"]:
if ocl.select_device(dtype=device):
test2d["lut_ocl_%s" % device] = self.eps
test2d["csr_ocl_%s" % device] = self.eps
test2d_direct = {"xrpd2_numpy": 0.3, # histograms are very noisy in 2D
"xrpd2_histogram": 0.3, # histograms are very noisy in 2D
"xrpd2_splitBBox": self.eps,
"xrpd2_splitPixel": self.eps}
for meth in test2d:
logger.info("About to test2d %s" % meth)
try:
I, _, _ = self.ai.integrate2d(self.raw, self.bins, self.azim, unit="r_mm", method=meth, correctSolidAngle=False, dark=self.dark, flat=self.flat)
except (MemoryError, pyFAI.opencl.pyopencl.MemoryError):
logger.warning("Got MemoryError from OpenCL device")
continue
I = I[numpy.where(I > 0)]
logger.info("2D method:%s Imin=%s Imax=%s <I>=%s std=%s" % (meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2, "Mean should be 1 in %s" % meth)
self.assert_(I.max() - I.min() < test2d[meth], "deviation should be small with meth %s, got %s" % (meth, I.max() - I.min()))
for meth in test2d_direct:
logger.info("About to test2d_direct %s" % meth)
I, _, _ = self.ai.__getattribute__(meth)(self.raw, self.bins, self.azim, correctSolidAngle=False, dark=self.dark, flat=self.flat)
I = I[numpy.where(I > 0)]
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" % (meth, I.min(), I.max(), I.mean(), I.std()))
self.assert_(abs(I.mean() - 1) < test2d_direct[meth], "Mean should be 1 in %s" % meth)
self.assert_(I.max() - I.min() < test2d_direct[meth], "deviation should be small with meth %s, got %s" % (meth, I.max() - I.min()))
def test_correct(self):
all_methods = [
"numpy", "cython", "splitbbox", "splitpix", "lut", "csr"
]
if ocl:
for device in ["cpu", "gpu", "acc"]:
if ocl.select_device(dtype=device):
all_methods.append("lut_ocl_%s" % device)
all_methods.append("csr_ocl_%s" % device)
for meth in all_methods:
r, I = self.ai.integrate1d(self.raw,
self.bins,
unit="r_mm",
method=meth,
correctSolidAngle=False,
dark=self.dark,
flat=self.flat)
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" %
(meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2,
"Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < self.eps,
"deviation should be small with meth %s, got %s" %
(meth, I.max() - I.min()))
for meth in [
"xrpd_numpy", "xrpd_cython", "xrpd_splitBBox",
"xrpd_splitPixel"
]: # , "xrpd_OpenCL" ]: bug with 32 bit GPU and request 64 bit integration
r, I = self.ai.__getattribute__(meth)(self.raw,
self.bins,
correctSolidAngle=False,
dark=self.dark,
flat=self.flat)
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" %
(meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2,
"Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < self.eps,
"deviation should be small with meth %s, got %s" %
(meth, I.max() - I.min()))
if ocl and pyFAI.opencl.ocl.select_device("gpu",
extensions=["cl_khr_fp64"]):
meth = "xrpd_OpenCL"
r, I = self.ai.__getattribute__(meth)(self.raw,
self.bins,
correctSolidAngle=False,
dark=self.dark,
flat=self.flat)
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" %
(meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2,
"Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < self.eps,
"deviation should be small with meth %s, got %s" %
(meth, I.max() - I.min()))
def test_OpenCL_LUT(self):
logger.info("Testing LUT-based algorithm (backward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype, best=True)
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " %
(devtype, ids, ocl.platforms[ids[0]],
ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
ref = ai.integrate1d(data,
self.N,
method="splitBBox",
unit="2th_deg")
try:
res = ai.integrate1d(data,
self.N,
method="ocl_lut_%i,%i" %
(ids[0], ids[1]),
unit="2th_deg")
except (pyFAI.opencl.pyopencl.MemoryError, MemoryError,
pyFAI.opencl.pyopencl.RuntimeError,
RuntimeError) as error:
logger.warning(
"Memory error on %s dataset %s: %s%s. Converted into warnining: device may not have enough memory."
% (devtype, os.path.basename(
ds["img"]), os.linesep, error))
break
else:
ref = ai.xrpd(data, self.N)
r = Rwp(ref, res)
logger.info(
"OpenCL CSR vs histogram SplitBBox has R= %.3f for dataset %s"
% (r, ds))
self.assertTrue(
r < 3,
"Rwp=%.3f for OpenCL LUT processing of %s" % (r, ds))
del ai, data
gc.collect()
def test_correct(self):
all_methods = ["numpy", "cython", "splitbbox", "splitpix", "lut", "csr"]
if ocl:
for device in ["cpu", "gpu", "acc"]:
if ocl.select_device(dtype=device):
all_methods.append("lut_ocl_%s" % device)
all_methods.append("csr_ocl_%s" % device)
for meth in all_methods:
r, I = self.ai.integrate1d(
self.raw, self.bins, unit="r_mm", method=meth, correctSolidAngle=False, dark=self.dark, flat=self.flat
)
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" % (meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2, "Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < self.eps,
"deviation should be small with meth %s, got %s" % (meth, I.max() - I.min()),
)
for meth in [
"xrpd_numpy",
"xrpd_cython",
"xrpd_splitBBox",
"xrpd_splitPixel",
]: # , "xrpd_OpenCL" ]: bug with 32 bit GPU and request 64 bit integration
r, I = self.ai.__getattribute__(meth)(
self.raw, self.bins, correctSolidAngle=False, dark=self.dark, flat=self.flat
)
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" % (meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2, "Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < self.eps,
"deviation should be small with meth %s, got %s" % (meth, I.max() - I.min()),
)
if ocl and pyFAI.opencl.ocl.select_device("gpu", extensions=["cl_khr_fp64"]):
meth = "xrpd_OpenCL"
r, I = self.ai.__getattribute__(meth)(
self.raw, self.bins, correctSolidAngle=False, dark=self.dark, flat=self.flat
)
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" % (meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2, "Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < self.eps,
"deviation should be small with meth %s, got %s" % (meth, I.max() - I.min()),
)
def test_OpenCL(self):
logger.info("Testing histogram-based algorithm (forward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype, extensions=["cl_khr_int64_base_atomics"])
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " % (devtype, ids, ocl.platforms[ids[0]], ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
res = ai.xrpd_OpenCL(data, self.N, devicetype="all", platformid=ids[0], deviceid=ids[1], useFp64=True)
ref = ai.integrate1d(data, self.N, method="splitBBox", unit="2th_deg")
r = Rwp(ref, res)
logger.info("OpenCL histogram vs histogram SplitBBox has R= %.3f for dataset %s" % (r, ds))
self.assertTrue(r < 6, "Rwp=%.3f for OpenCL histogram processing of %s" % (r, ds))
del ai, data
gc.collect()
def test_OpenCL_LUT(self):
logger.info("Testing LUT-based algorithm (backward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype, best=True)
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " %
(devtype, ids, ocl.platforms[ids[0]],
ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
try:
res = ai.xrpd_LUT_OCL(data,
1000,
devicetype="all",
platformid=ids[0],
deviceid=ids[1])
except MemoryError as error:
logger.warning(
"Memory Error on %s dataset %s: %s%s. Converted into warnining: device may not have enough memory."
% (devtype, os.path.basename(
ds["img"]), os.linesep, error))
else:
t0 = time.time()
ref = ai.xrpd(data, 1000)
t1 = time.time()
res = ai.xrpd_LUT_OCL(data, 1000, safe=False)
t2 = time.time()
logger.info(
"For image %15s;\tspeed up is %.3fx;\trate is %.3f Hz"
% (os.path.basename(ds["img"]),
((t1 - t0) / (t2 - t1)), 1. / (t2 - t1)))
r = Rwp(ref, res)
self.assertTrue(
r < 10,
"Rwp=%.3f for OpenCL processing of %s" % (r, ds))
def test_OpenCL(self):
logger.info("Testing histogram-based algorithm (forward-integration)")
for devtype in ("GPU", "CPU"):
ids = ocl.select_device(devtype, extensions=["cl_khr_int64_base_atomics"])
if ids is None:
logger.error("No suitable %s OpenCL device found" % devtype)
continue
else:
logger.info("I found a suitable device %s %s: %s %s " % (devtype, ids, ocl.platforms[ids[0]], ocl.platforms[ids[0]].devices[ids[1]]))
for ds in self.datasets:
ai = pyFAI.load(ds["poni"])
data = fabio.open(ds["img"]).data
res = ai.xrpd_OpenCL(data, 1000, devicetype="all", platformid=ids[0], deviceid=ids[1], useFp64=True)
t0 = time.time()
ref = ai.xrpd(data, 1000)
t1 = time.time()
res = ai.xrpd_OpenCL(data, 1000, safe=False)
t2 = time.time()
logger.info("For image %15s;\tspeed up is %.3fx;\trate is %.3f Hz" % (os.path.basename(ds["img"]), ((t1 - t0) / (t2 - t1)), 1. / (t2 - t1)))
r = Rwp(ref, res)
self.assertTrue(r < 10, "Rwp=%.3f for OpenCL processing of %s" % (r, ds))
def test_correct(self):
test2d = {
"numpy": self.eps,
"cython": self.eps,
"splitbbox": self.eps,
"splitpix": self.eps,
"lut": self.eps,
}
if ocl:
for device in ["cpu", "gpu", "acc"]:
if ocl.select_device(dtype=device):
test2d["lut_ocl_%s" % device] = self.eps
test2d["csr_ocl_%s" % device] = self.eps
test2d_direct = {
"xrpd2_numpy": 0.3, # histograms are very noisy in 2D
"xrpd2_histogram": 0.3, # histograms are very noisy in 2D
"xrpd2_splitBBox": self.eps,
"xrpd2_splitPixel": self.eps
}
for meth in test2d:
logger.info("About to test2d %s" % meth)
try:
I, _, _ = self.ai.integrate2d(self.raw,
self.bins,
self.azim,
unit="r_mm",
method=meth,
correctSolidAngle=False,
dark=self.dark,
flat=self.flat)
except (MemoryError, pyFAI.opencl.pyopencl.MemoryError):
logger.warning("Got MemoryError from OpenCL device")
continue
I = I[numpy.where(I > 0)]
logger.info("2D method:%s Imin=%s Imax=%s <I>=%s std=%s" %
(meth, I.min(), I.max(), I.mean(), I.std()))
self.assertAlmostEqual(I.mean(), 1, 2,
"Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < test2d[meth],
"deviation should be small with meth %s, got %s" %
(meth, I.max() - I.min()))
for meth in test2d_direct:
logger.info("About to test2d_direct %s" % meth)
I, _, _ = self.ai.__getattribute__(meth)(self.raw,
self.bins,
self.azim,
correctSolidAngle=False,
dark=self.dark,
flat=self.flat)
I = I[numpy.where(I > 0)]
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s" %
(meth, I.min(), I.max(), I.mean(), I.std()))
self.assert_(
abs(I.mean() - 1) < test2d_direct[meth],
"Mean should be 1 in %s" % meth)
self.assert_(
I.max() - I.min() < test2d_direct[meth],
"deviation should be small with meth %s, got %s" %
(meth, I.max() - I.min()))
