Fixed indentation
This commit is contained in:
Philippe Tillet
@@ -27,120 +27,120 @@ TYPES = { 'vector-axpy': {'template':vcl.atidlas.VectorAxpyTemplate,
|
||||
'parameter-names':['simd-width', 'local-size-0', 'num-groups-0', 'fetch'],
|
||||
'perf-index':lambda x: 3*x[0]*x[1][0]/x[2]*1e-9,
|
||||
'perf-measure':'GB/s'},
|
||||
|
||||
|
||||
'matrix-axpy': {'template':vcl.atidlas.MatrixAxpyTemplate,
|
||||
'parameter-names':['simd-width', 'local-size-0', 'local-size-1', 'num-groups-0', 'num-groups-1', 'fetch'],
|
||||
'perf-index':lambda x: 3*x[0]*x[1][0]*x[1][1]/x[2]*1e-9,
|
||||
'perf-measure':'GB/s'},
|
||||
|
||||
|
||||
'reduction': {'template':vcl.atidlas.ReductionTemplate,
|
||||
'parameter-names':['simd-width', 'local-size-0', 'num-groups-0', 'fetch'],
|
||||
'perf-index':lambda x: 2*x[0]*x[1][0]*x[1][1]/x[2]*1e-9,
|
||||
'perf-measure':'GB/s'},
|
||||
|
||||
|
||||
'row-wise-reduction': {'template':vcl.atidlas.RowWiseReductionTemplate,
|
||||
'parameter-names':['simd-width', 'local-size-0', 'local-size-1', 'num-groups-0', 'fetch'],
|
||||
'perf-index':lambda x: x[0]*x[1][0]*x[1][1]/x[2]*1e-9,
|
||||
'perf-measure':'GB/s'},
|
||||
|
||||
|
||||
'matrix-product': {'template':vcl.atidlas.MatrixProductTemplate,
|
||||
'parameter-names':['simd-width', 'local-size-0', 'kL', 'local-size-1', 'mS', 'kS', 'nS', 'A-fetch-policy', 'B-fetch-policy', 'local-fetch-size-0', 'local-fetch-size-1'],
|
||||
'perf-index': lambda x: 2*x[1][0]*x[1][1]*x[1][2]/x[2]*1e-9,
|
||||
'perf-measure': 'GFLOP/s'} }
|
||||
|
||||
def do_tuning(config_fname, spec_fname, viennacl_root):
|
||||
config = ConfigObj(config_fname, configspec=spec_fname)
|
||||
map_to_list = lambda T: list(map(T[0], T[1] if isinstance(T[1], list) else [T[1]]))
|
||||
for operation in ['vector-axpy', 'matrix-axpy', 'row-wise-reduction', 'matrix-product']:
|
||||
if operation in config:
|
||||
p = config[operation]
|
||||
confdevices = p['devices']
|
||||
devices = utils.DEVICES_PRESETS[confdevices] if confdevices in utils.DEVICES_PRESETS else [utils.all_devices[int(i)] for i in confdevices]
|
||||
precisions = map_to_list((str, p['precision']))
|
||||
datatypes = [DATATYPES[k] for k in precisions]
|
||||
#Iterate through the datatypes and the devices
|
||||
for datatype, device in itertools.product(datatypes, devices):
|
||||
ctx = cl.Context([device])
|
||||
ctx = vcl.backend.Context(ctx)
|
||||
device = ctx.current_device
|
||||
#Check data-type
|
||||
if datatype is vcl.float64 and not device.double_fp_config:
|
||||
sys.stderr.write('Warning : The device ' + device.name + ' does not support double precision! Skipping ...')
|
||||
continue
|
||||
#Helper
|
||||
def execute(statement, other_params, sizes, fname = os.devnull):
|
||||
print('-----')
|
||||
print(' '.join(map(str, ("Now tuning:", datatype.__name__, '-', operation, '-'.join(other_params), '[' + device.name, '(' + device.platform.name + ')] for sizes', sizes))))
|
||||
with open(fname, "w+") as archive:
|
||||
return optimize.genetic(statement, ctx, TYPES[operation]['template'], lambda p: TYPES[operation]['template'](p, *other_params),
|
||||
TYPES[operation]['parameter-names'], lambda t: TYPES[operation]['perf-index']([datatype().itemsize, sizes, t]), TYPES[operation]['perf-measure'], archive)
|
||||
s = map_to_list((int, p['size']))
|
||||
#Vector AXPY
|
||||
if operation=='vector-axpy':
|
||||
x = vcl.Vector(s[0], context=ctx, dtype=datatype)
|
||||
y = vcl.Vector(s[0], context=ctx, dtype=datatype)
|
||||
execute(vcl.ElementProd(vcl.exp(x + y),vcl.cos(x + y)), ())
|
||||
#Matrix AXPY
|
||||
if operation=='matrix-axpy':
|
||||
A = vcl.Matrix(s, context=ctx, dtype=datatype)
|
||||
B = vcl.Matrix(s, context=ctx, dtype=datatype)
|
||||
execute(A+B, ())
|
||||
#Row-wise reduction
|
||||
if operation=='row-wise-reduction':
|
||||
layouts = map_to_list((str,p['layout']))
|
||||
if 'all' in layouts:
|
||||
layouts = ['N', 'T']
|
||||
for A_trans in layouts:
|
||||
A = vcl.Matrix(s if A_trans=='N' else s[::-1], context=ctx, dtype=datatype, layout=vcl.COL_MAJOR)
|
||||
x = vcl.Vector(s[1] if A_trans=='N' else s[0], context=ctx, dtype=datatype)
|
||||
LHS = A if A_trans=='N' else A.T
|
||||
execute(LHS*x, ())
|
||||
#Matrix Product
|
||||
if operation=='matrix-product':
|
||||
layouts = map_to_list((str,p['layout']))
|
||||
if 'all' in layouts:
|
||||
layouts = ['NN', 'NT', 'TN', 'TT']
|
||||
for layout in layouts:
|
||||
def execution_handler(sizes, fname, parameters=None):
|
||||
A_trans = layout[0]
|
||||
B_trans = layout[1]
|
||||
A = vcl.Matrix((sizes[0], sizes[1]) if A_trans=='N' else (sizes[1],sizes[0]), context=ctx, dtype=datatype, layout=vcl.COL_MAJOR);
|
||||
B = vcl.Matrix((sizes[1], sizes[2]) if B_trans=='N' else (sizes[2],sizes[1]), context=ctx, dtype=datatype, layout=vcl.COL_MAJOR);
|
||||
LHS = A if A_trans=='N' else A.T
|
||||
RHS = B if B_trans=='N' else B.T
|
||||
alpha = vcl.HostScalar(1.0, context=ctx, dtype = datatype)
|
||||
beta = vcl.HostScalar(1.0, context=ctx, dtype = datatype)
|
||||
C = vcl.Matrix((sizes[0], sizes[2]), context=ctx, dtype = datatype, layout=vcl.COL_MAJOR)
|
||||
statement = vcl.Statement(vcl.Assign(C,LHS*RHS*alpha + C*beta))
|
||||
if parameters:
|
||||
TemplateType = TYPES[operation]['template']
|
||||
return tools.benchmark(TemplateType(TemplateType.Parameters(*parameters),A_trans,B_trans), statement, device)
|
||||
else:
|
||||
execute(statement,(A_trans, B_trans), sizes, fname)
|
||||
X, Y, profiles = generate_dataset(TYPES[operation]['template'], execution_handler)
|
||||
train_model(X, Y, profiles)
|
||||
|
||||
|
||||
|
||||
def do_tuning(config_fname, spec_fname, viennacl_root):
|
||||
config = ConfigObj(config_fname, configspec=spec_fname)
|
||||
map_to_list = lambda T: list(map(T[0], T[1] if isinstance(T[1], list) else [T[1]]))
|
||||
for operation in ['vector-axpy', 'matrix-axpy', 'row-wise-reduction', 'matrix-product']:
|
||||
if operation in config:
|
||||
p = config[operation]
|
||||
confdevices = p['devices']
|
||||
devices = utils.DEVICES_PRESETS[confdevices] if confdevices in utils.DEVICES_PRESETS else [utils.all_devices[int(i)] for i in confdevices]
|
||||
precisions = map_to_list((str, p['precision']))
|
||||
datatypes = [DATATYPES[k] for k in precisions]
|
||||
#Iterate through the datatypes and the devices
|
||||
for datatype, device in itertools.product(datatypes, devices):
|
||||
ctx = cl.Context([device])
|
||||
ctx = vcl.backend.Context(ctx)
|
||||
device = ctx.current_device
|
||||
#Check data-type
|
||||
if datatype is vcl.float64 and not device.double_fp_config:
|
||||
sys.stderr.write('Warning : The device ' + device.name + ' does not support double precision! Skipping ...')
|
||||
continue
|
||||
#Helper
|
||||
def execute(statement, other_params, sizes, fname = os.devnull):
|
||||
print('-----')
|
||||
print(' '.join(map(str, ("Now tuning:", datatype.__name__, '-', operation, '-'.join(other_params), '[' + device.name, '(' + device.platform.name + ')] for sizes', sizes))))
|
||||
with open(fname, "w+") as archive:
|
||||
return optimize.genetic(statement, ctx, TYPES[operation]['template'], lambda p: TYPES[operation]['template'](p, *other_params),
|
||||
TYPES[operation]['parameter-names'], lambda t: TYPES[operation]['perf-index']([datatype().itemsize, sizes, t]), TYPES[operation]['perf-measure'], archive)
|
||||
s = map_to_list((int, p['size']))
|
||||
#Vector AXPY
|
||||
if operation=='vector-axpy':
|
||||
x = vcl.Vector(s[0], context=ctx, dtype=datatype)
|
||||
y = vcl.Vector(s[0], context=ctx, dtype=datatype)
|
||||
execute(vcl.ElementProd(vcl.exp(x + y),vcl.cos(x + y)), ())
|
||||
#Matrix AXPY
|
||||
if operation=='matrix-axpy':
|
||||
A = vcl.Matrix(s, context=ctx, dtype=datatype)
|
||||
B = vcl.Matrix(s, context=ctx, dtype=datatype)
|
||||
execute(A+B, ())
|
||||
#Row-wise reduction
|
||||
if operation=='row-wise-reduction':
|
||||
layouts = map_to_list((str,p['layout']))
|
||||
if 'all' in layouts:
|
||||
layouts = ['N', 'T']
|
||||
for A_trans in layouts:
|
||||
A = vcl.Matrix(s if A_trans=='N' else s[::-1], context=ctx, dtype=datatype, layout=vcl.COL_MAJOR)
|
||||
x = vcl.Vector(s[1] if A_trans=='N' else s[0], context=ctx, dtype=datatype)
|
||||
LHS = A if A_trans=='N' else A.T
|
||||
execute(LHS*x, ())
|
||||
#Matrix Product
|
||||
if operation=='matrix-product':
|
||||
layouts = map_to_list((str,p['layout']))
|
||||
if 'all' in layouts:
|
||||
layouts = ['NN', 'NT', 'TN', 'TT']
|
||||
for layout in layouts:
|
||||
def execution_handler(sizes, fname, parameters=None):
|
||||
A_trans = layout[0]
|
||||
B_trans = layout[1]
|
||||
A = vcl.Matrix((sizes[0], sizes[1]) if A_trans=='N' else (sizes[1],sizes[0]), context=ctx, dtype=datatype, layout=vcl.COL_MAJOR);
|
||||
B = vcl.Matrix((sizes[1], sizes[2]) if B_trans=='N' else (sizes[2],sizes[1]), context=ctx, dtype=datatype, layout=vcl.COL_MAJOR);
|
||||
LHS = A if A_trans=='N' else A.T
|
||||
RHS = B if B_trans=='N' else B.T
|
||||
alpha = vcl.HostScalar(1.0, context=ctx, dtype = datatype)
|
||||
beta = vcl.HostScalar(1.0, context=ctx, dtype = datatype)
|
||||
C = vcl.Matrix((sizes[0], sizes[2]), context=ctx, dtype = datatype, layout=vcl.COL_MAJOR)
|
||||
statement = vcl.Statement(vcl.Assign(C,LHS*RHS*alpha + C*beta))
|
||||
if parameters:
|
||||
TemplateType = TYPES[operation]['template']
|
||||
return tools.benchmark(TemplateType(TemplateType.Parameters(*parameters),A_trans,B_trans), statement, device)
|
||||
else:
|
||||
execute(statement,(A_trans, B_trans), sizes, fname)
|
||||
X, Y, profiles = generate_dataset(TYPES[operation]['template'], execution_handler)
|
||||
train_model(X, Y, profiles)
|
||||
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser();
|
||||
subparsers = parser.add_subparsers(dest='action')
|
||||
print_devices_parser = subparsers.add_parser('list-devices', help='list the devices available')
|
||||
tune_parser = subparsers.add_parser('tune', help='tune using a specific configuration file')
|
||||
tune_parser.add_argument("--config", default="config.ini", required=False, type=str)
|
||||
tune_parser.add_argument("--viennacl-root", default='', required=False, type=str)
|
||||
args = parser.parse_args()
|
||||
|
||||
if(args.action=='list-devices'):
|
||||
print("----------------")
|
||||
print("Devices available:")
|
||||
print("----------------")
|
||||
devices = [d for platform in cl.get_platforms() for d in platform.get_devices()]
|
||||
for (i, d) in enumerate(devices):
|
||||
print('Device', i, ':', utils.DEVICE_TYPE_PREFIX[d.type].upper() + ':', d.name, 'on', d.platform.name)
|
||||
print("----------------")
|
||||
else:
|
||||
print("------")
|
||||
print("Auto-tuning")
|
||||
print("------")
|
||||
do_tuning(args.config, 'config_spec.ini', args.viennacl_root)
|
||||
parser = argparse.ArgumentParser();
|
||||
subparsers = parser.add_subparsers(dest='action')
|
||||
print_devices_parser = subparsers.add_parser('list-devices', help='list the devices available')
|
||||
tune_parser = subparsers.add_parser('tune', help='tune using a specific configuration file')
|
||||
tune_parser.add_argument("--config", default="config.ini", required=False, type=str)
|
||||
tune_parser.add_argument("--viennacl-root", default='', required=False, type=str)
|
||||
args = parser.parse_args()
|
||||
|
||||
if(args.action=='list-devices'):
|
||||
print("----------------")
|
||||
print("Devices available:")
|
||||
print("----------------")
|
||||
devices = [d for platform in cl.get_platforms() for d in platform.get_devices()]
|
||||
for (i, d) in enumerate(devices):
|
||||
print('Device', i, ':', utils.DEVICE_TYPE_PREFIX[d.type].upper() + ':', d.name, 'on', d.platform.name)
|
||||
print("----------------")
|
||||
else:
|
||||
print("------")
|
||||
print("Auto-tuning")
|
||||
print("------")
|
||||
do_tuning(args.config, 'config_spec.ini', args.viennacl_root)
|
||||
|
||||
Reference in New Issue
Block a user