少有人走的路
* Determine the multithreading information
get_multithreading_operators (TypeExclusive, TypeMutual, TypeReentrant, TypeIndependent)
* 自定义函数展开之后,有get_operator_info算子
* get names of all operators of the library
get_operator_name ('', OperatorNames)
get_operator_info (OperatorNames[Index], 'parallelization', Information)来自官方例程query_system_parameters.hdev
* Parallelization
get_system ('processor_num', ProcessorNum)
get_system ('thread_pool', ThreadPool)
get_system ('thread_num', ThreadNum)
*Automatic Operator Parallelization,默认值是true
get_system ('parallelize_operators', AOP)
*这个修饰符用于把函数定义为可重入函数,默认值是true;所谓可重入函数就是允许被递归调用的函数
get_system ('reentrant', Reentrant)
*故意关掉测试性能
*set_system('parallelize_operators','false')* Determine the parallelization method of all parallelized operators
get_parallel_method_operators (SplitTuple, SplitChannel, SplitDomain, SplitPartial, None)
AutoParallel := [SplitTuple,SplitChannel,SplitDomain,SplitPartial]
AutoParallel := uniq(sort(AutoParallel))
* 自定义函数展开之后,有get_operator_info算子
* get names of all operators of the library
get_operator_name ('', OperatorNames)
get_operator_info (OperatorNames[Index], 'parallel_method', Information)5、如果程序员不想使用AOP，而是自己实现并行化，那较为复杂，需要使用多线程技术，把图像进行拆分处理，最后再合并。因此需要更多专业知识，详情参见官方例程simulate_aop.hdev和官方说明书parallel_programming.pdf。
*set_system('parallelize_operators','false')来自官方例程compute_devices.hdev * This example shows how to use compute devices with HALCON. * dev_update_off () dev_close_window () dev_open_window_fit_size (0, 0, 640, 480, -1, -1, WindowHandle) set_display_font (WindowHandle, 16, 'mono', 'true', 'false') * * Get list of all available compute devices. query_available_compute_devices (DeviceIdentifier) * * End example if no device could be found. if (|DeviceIdentifier| == 0) return () endif * * Display basic information on detected devices. disp_message (WindowHandle, 'Found ' + |DeviceIdentifier| + ' Compute Device(s):', 'window', 12, 12, 'black', 'true') for Index := 0 to |DeviceIdentifier| - 1 by 1 get_compute_device_info (DeviceIdentifier[Index], 'name', DeviceName) get_compute_device_info (DeviceIdentifier[Index], 'vendor', DeviceVendor) Message[Index] := 'Device #' + Index + ': ' + DeviceVendor + ' ' + DeviceName endfor disp_message (WindowHandle, Message, 'window', 42, 12, 'white', 'false') disp_continue_message (WindowHandle, 'black', 'true') stop ()
* Determine all operators that support OpenCL
get_opencl_operators (OpenCLSupport)
* 自定义函数展开之后,有get_operator_info算子
get_operator_name ('', OperatorNames)
get_operator_info (OperatorNames[Index], 'compute_device', Information)*参考官方例程optimize_aop.hdev;query_aop_info.hdev;simulate_aop.hdev;
*举例edges_sub_pix算子性能测试
dev_update_off ()//实现提速的优良效果，必须先关闭设备
dev_close_window ()
dev_open_window_fit_size (0, 0, 640, 480, -1, -1, WindowHandle)
set_display_font (WindowHandle, 16, 'mono', 'true', 'false')
get_system ('processor_num', NumCPUs)
get_system ('parallelize_operators', AOP)
*读取图片
read_image(Image, 'D:/hellowprld/2/1-.jpg')
*彩色转灰度图
count_channels (Image, Channels)
if (Channels == 3 or Channels == 4)
rgb1_to_gray (Image, ImageGray)
endif
alpha:=5
low:=10
high:=20
*测试1:去掉AOP,即没有加速并行处理
set_system ('parallelize_operators', 'false')
get_system ('parallelize_operators', AOP)
count_seconds(T0)
edges_sub_pix (ImageGray, Edges1, 'canny', alpha, low, high)
count_seconds(T1)
Time0:=(T1-T0)*1000
stop()
*测试2:AOP自动加速并行处理
*Halcon的默认值是开启AOP的,即parallelize_operators值为true
set_system ('parallelize_operators', 'true')
count_seconds(T1)
edges_sub_pix (ImageGray, Edges1, 'canny', alpha, low, high)
count_seconds(T2)
Time1:=(T2-T1)*1000
stop()
*测试3:GPU加速，支持GPU加速的算子Halcon19.11有82个
*GPU加速是先从CPU中将数据拷贝到GPU上处理，处理完成后再将数据从GPU拷贝到CPU上。从CPU到GPU再从GPU到CPU是要花费时间的。
*GPU加速一定会比正常的AOP运算速度快吗?不一定!结果取决于显卡的好坏.
query_available_compute_devices(DeviceIdentifiers)
DeviceHandle:=0
for i:=0 to |DeviceIdentifiers|-1 by 1
get_compute_device_info(DeviceIdentifiers[i], 'name', Nmae)
if (Nmae == 'GeForce GT 630')//根据GPU名称打开GPU
open_compute_device(DeviceIdentifiers[i], DeviceHandle)
break
endif
endfor
if(DeviceHandle#0)
set_compute_device_param (DeviceHandle, 'asynchronous_execution', 'false')
init_compute_device(DeviceHandle, 'edges_sub_pix')
activate_compute_device(DeviceHandle)
endif
*获得显卡的信息
get_compute_device_param (DeviceHandle, 'buffer_cache_capacity', GenParamValue0)//默认值是显卡缓存的1/3
get_compute_device_param (DeviceHandle, 'buffer_cache_used', GenParamValue1)
get_compute_device_param (DeviceHandle, 'image_cache_capacity', GenParamValue2)
get_compute_device_param (DeviceHandle, 'image_cache_used', GenParamValue3)
*GenParamValue0 := GenParamValue0 / 3
*set_compute_device_param (DeviceHandle, 'buffer_cache_capacity', GenParamValue0)
*get_compute_device_param (DeviceHandle, 'buffer_cache_capacity', GenParamValue4)
count_seconds(T3)
*如果显卡缓存不够,会报错,error #4104 : Out of compute device memory
edges_sub_pix (ImageGray, Edges1, 'canny', alpha, low, high)
count_seconds(T4)
Time2:=(T4-T3)*1000
if(DeviceHandle#0)
deactivate_compute_device(DeviceHandle)
endif
stop()
*测试4:AOP手动优化
set_system ('parallelize_operators', 'true')
get_system ('parallelize_operators', AOP)
*4.1-优化线程数目方法'threshold'
optimize_aop ('edges_sub_pix', 'byte', 'no_file', ['file_mode','model','parameters'], ['nil','threshold','false'])
count_seconds(T5)
edges_sub_pix (ImageGray, Edges1, 'canny', alpha, low, high)
count_seconds(T6)
Time3:=(T6-T5)*1000
*4.2-优化线程数目方法'linear'
optimize_aop ('edges_sub_pix', 'byte', 'no_file', ['file_mode','model','parameters'], ['nil','linear','false'])
count_seconds(T7)
edges_sub_pix (ImageGray, Edges1, 'canny', alpha, low, high)
count_seconds(T8)
Time4:=(T8-T7)*1000
stop()
*4.3-优化线程数目方法'mlp'
optimize_aop ('edges_sub_pix', 'byte', 'no_file', ['file_mode','model','parameters'], ['nil','mlp','false'])
count_seconds(T9)
edges_sub_pix (ImageGray, Edges1, 'canny', alpha, low, high)
count_seconds(T10)
Time5:=(T10-T9)*1000
stop()
dev_clear_window()
Message := 'edges_sub_pix runtimes:'
Message[1] := 'CPU only Time0 without AOP='+Time0+'ms,'
Message[2] := 'CPU only Time1 with AOP='+Time1+'ms,'
Message[3] := 'GPU use Time2='+Time2+'ms,'
Message[4] := 'optimize Time3 threshold='+Time3+'ms'
Message[5] := 'optimize Time4 linear='+Time4+'ms'
Message[6] := 'optimize Time5 mlp='+Time5+'ms'
disp_message (WindowHandle, Message, 'window', 12, 12, 'red', 'false')
stop()edges_sub_pix算子性能测试结果：
rotate_image算子性能测试结果：
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