A scheduling framework based on OpenCL kernel tasks

A task and kernel technology, applied in the field of computer applications, can solve problems such as increasing the burden on programmers and experience requirements

Pending Publication Date: 2019-03-29
XI AN JIAOTONG UNIV
View PDF6 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in order to make full use of the computing resources of PE (Processing Elements) in the target device and write more efficient codes, programme

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A scheduling framework based on OpenCL kernel tasks
  • A scheduling framework based on OpenCL kernel tasks
  • A scheduling framework based on OpenCL kernel tasks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] The purpose of the present invention is to provide a scheduling framework suitable for CPU / GPU heterogeneous environment, which automatically performs task division prediction and task scheduling. The framework includes two stages and three parts, compilation stage and scheduling stage, feature selection, task division prediction and the three parts of the scheduling algorithm, as shown in the attached figure 1 shown. The framework can realize automatic task scheduling in a heterogeneous environment, improve the resource utilization of heterogeneous platforms, and reduce the workload and experience requirements of parallel programming developers.

[0025] In order to achieve the above object, a kind of scheduling frame based on OpenCL kernel task of the present invention adopts following technical scheme:

[0026] The OpenCL kernel task scheduling framework is developed based on the OpenCL parallel programming language, using Clang and LLVM compilers for the feature ex...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a scheduling framework based on OpenCL kernel tasks. The framework includes the feature extraction and feature selection of OpenCL kernel tasks by LLVM compiler, and the compile-time static and run-time features of kernel code are obtained. In the process of feature extraction, the Greedy Feature Selection algorithm is used to select the most important features to avoid over-fitting. Then the selected features are used to predict the task partition ratio between CPU and GPU by using the static classifier in machine learning. At last, the scheduling algorithm is used todivide the tasks into proportions and the available equipment information of the platform, The invention completes the design details of the functions, realizes the algorithm and coding work, realizesthe automatic scheduling of maximizing the utilization of computing resources in the heterogeneous system through the combination of machine learning and scheduling algorithm, and improves the utilization rate of the heterogeneous system resources.

Description

technical field [0001] The invention belongs to the field of computer applications, and in particular relates to a task scheduling framework for realizing task division by using a machine learning method in a heterogeneous system. Background technique [0002] In the past ten years, major processor manufacturers have paid close attention to the field of high-performance computing and tried to develop the latest and most cutting-edge computing accelerator cards. Acceleration cards such as GPUs and FPGAs developed by Intel, Nvidia, and AMD are widely used in various fields. Heterogeneous computing technology has been produced in the 1980s and has the characteristics of high performance and good scalability. In addition, with the current hot accelerator card market and the development of artificial intelligence technology, heterogeneous computing has become one of the research hotspots in the field of parallel computing and distributed computing. [0003] For computing-intens...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F9/48G06F9/50G06N20/00
CPCG06F9/4881G06F9/5027Y02D10/00
Inventor 朱正东张小雨韩靖雯李少辉郭辉李小轩王鹏博田靖轩
Owner XI AN JIAOTONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap