Abstract:
A data processing system, a computing node, and a data processing method are provided. The data processing system includes a management node and a first class of computing nodes. The management node is configured to allocate first processing tasks to the first class of computing nodes. At least two computing nodes in the first class of computing nodes concurrently perform the first processing tasks allocated by the management node. A computing node performs a combine2 operation and a reduce2 operation on a data block Mx and a data block V1x, to obtain a first intermediate result. Then, the management node obtains a processing result for a to-be-processed dataset according to first intermediate results obtained by the first class of computing nodes. According to the data processing system, when a combine operation and a reduce operation are being performed on data blocks, memory space occupied by computation can be reduced.
Abstract:
An on-chip memory in a many-core system is partitioned, and according to a frequency at which a processor core set in each on-chip partition accesses a virtual memory page in virtual memory space that is shared among multiple processes that belong to a same application program, data corresponding to the virtual memory page is moved to an on-chip memory partition in which a processor core set whose access frequency is high is located such that when the virtual memory page is subsequently accessed, a time delay caused by cross-partition access is reduced.
Abstract:
A method and a related device for determining a management mode of a shared virtual memory page are disclosed. In one example, a method is disclosed that includes monitoring frequency or mode of access operation of at least one process accessing the shared virtual memory page; and changing the management mode of the shared virtual memory page to a shared physical memory mode if the monitored frequency or mode of access operation meets a first set condition and a current management mode of the shared virtual memory page is a distributed shared memory mode. The technical solutions provided in the present disclosure can enhance performance of accessing a shared virtual memory.
Abstract:
Embodiments of the present invention provide an open application programming interface selection method and device. The method includes: receiving an invocation request from a user, where the invocation request includes an OpenAPI function parameter; determining an OpenAPI equivalent set according to the OpenAPI function parameter; and selecting a target OpenAPI from multiple OpenAPIs according to a Qos attribute value that corresponds to each OpenAPI in the OpenAPI equivalent set. By adopting the embodiments of the present invention, an OpenAPI with better performance can be selected from numerous OpenAPIs with equivalent functions for a user, thereby improving the quality of service for the user.
Abstract:
An instance segmentation method and apparatus are provided. A to-be-trained segmentation network performs the following processing on each instance group that is in a sample original image and that is of pixels of a marked instance, where each instance group includes at least one marked instance, and the processing includes: predicting at least two different first basic feature maps and a first attention feature map corresponding to each first basic feature map; performing weighted processing on the at least two first basic feature maps and pixel values of respective first attention feature maps corresponding to the at least two first basic feature maps, to obtain a first feature fusion map; and training the to-be-trained segmentation network based on the first feature fusion map and the sample original image. A segmentation model can precisely determine pixels of an instance in an original image.
Abstract:
Example methods, apparatuses, and computer program products for processing images by using a convolutional neural network (CNN) are described herein. In one example, an original image is received from an image source. The original image has a predefined size and high resolution, and is represented in a first color space supported by the image source. Then, an intermediate image is obtained by downscaling the original image in the first color space, and converted from the first color space to a second color space. Next, a restored image is obtained by upscaling the converted intermediate image to the predefined size of the original image. Upscaling is performed by using the CNN on the original image and the converted intermediate image as inputs and return the restored image. The CNN is pre-trained on a set of triplets, comprising a past original image, a converted past intermediate image and a past restored image.
Abstract:
An image processing method. The method includes: An electronic device obtains N images, where the N images have a same quantity of pixels and a same pixel location arrangement, and N is an integer greater than 1; the electronic device obtains, based on feature values of pixels located at a same location in the N images, a reference value of the corresponding location; the electronic device determines a target pixel of each location based on a reference value of the location; and the electronic device generates a target image based on the target pixel of each location.
Abstract:
In a method for selecting pictures from a sequence of pictures of an object in motion, a computerized user device determines, for each picture in the sequence of pictures, a value of a motion feature of the object. Based on analyzing the values of the motion feature of the pictures in the sequence, the device identifies a first subset of pictures from the pictures in the sequence. The device then selects, based on a second selection criterion, a second subset of pictures from the first subset of pictures. The pictures in the second subset are displayed to a user for further selection.
Abstract:
The present disclosure relates to a multicore processor. In order to select one of a multiplicity of cores in a multicore processor, an execution time of tasks which are performed multiple times is determined. Based on the determined execution time on the individual cores, an appropriate core for further executions of a task is selected. Additionally, the present disclosure further provides a code generator and code generating method for providing appropriate machine code for a multicore processor.
Abstract:
A multicore processor is provided. In order to select one of the multiple cores in such a multicore processor, an execution time of tasks which are performed multiple times is determined. Based on the determined execution time on the individual cores, an appropriate core for further executions of a task is selected. Additionally, the present disclosure further provides a code generator and code generating method for providing appropriate machine code for the multicore processor.