当前位置:网站首页>Co create a collaborative ecosystem of software and hardware: the "Joint submission" of graphcore IPU and Baidu PaddlePaddle appeared in mlperf
Co create a collaborative ecosystem of software and hardware: the "Joint submission" of graphcore IPU and Baidu PaddlePaddle appeared in mlperf
2022-07-07 13:35:00 【Paddlepaddle】
This article is already in Flying propeller The official account is issued , Please check the link :
Create a collaborative ecosystem of software and hardware :Graphcore IPU With Baidu PaddlePaddle “ Joint submission ” Appearance MLPerf
AI The most famous industrial benchmark list in the field MLPerf Training 2.0 On 6 month 30 Official release . In this list , Baidu Flying propeller And Graphcore cooperation , stay MLPerf It opens an innovative “ Joint submission ” Pattern .
“ Joint submission ” Appearance MLPerf
This time MLPerf Training v2.0 in , Baidu Flying propeller And Graphcore Cooperation has an innovative result submission mode :Graphcore Use the same software and hardware configuration as Baidu (Graphcore IPU and Flying propeller Deep learning framework ) submitted MLPerf BERT Achievements of the model . chart 1 Shows this Graphcore Use with Baidu IPU The submitted BERT Benchmark results , Flying propeller Performance and Graphcore Highly optimized self-developed framework PopART Performance is quite .
chart 1:MLPerf Training v2.0, Graphcore Submitted with Baidu BERT Model in Graphcore IPU Training performance results on . among , Red representative Graphcore Use the native framework PopART Achievements , Blue stands for Graphcore Use with Baidu Flying propeller Achievements of the framework .
“ Joint submission ”: Flying propeller A new attempt of hardware ecosystem CO creation plan
Baidu Flying propeller stay WAVE SUMMIT 2022 In depth learning developer Summit , Together with more than ten hardware manufacturers, we have released the hardware ecosystem CO creation plan . Flying propeller It will combine the features of the partner's own software and hardware development stack , For different application scenarios and products , Jointly launch the customized version of the manufacturer for the majority of developers Flying propeller frame 、 Build an open source model library 、 Develop courses and training contents, etc , Better serve developers , Achieve ecological prosperity and win-win results .
Baidu Flying propeller And Graphcore Cooperative MLPerf Joint submission , yes Flying propeller An innovative attempt of the hardware ecosystem CO creation plan . The two companies use the same software and hardware configuration to submit grades , This joint submission is in MLPerf For the first time in the competition . So , We are in the preparation stage with the organizer MLCommons Made detailed communication , To determine the feasibility of this submission . The results of this cooperation are gratifying , Not only the achievements of the technical cooperation between the two sides passed MLPerf Introduce to global developers , This soft and hard cooperation submission mode is also in MLPerf The media communication meeting was praised by representatives of other manufacturers .
“ Joint submission ” Behind the technical cooperation
For this time MLPerf Joint submission , Baidu Flying propeller And Graphcore Deep collaborative optimization , It is mainly reflected in the following aspects :
Optimize parallelism
Optimize the model segmentation strategy , So as to improve the parallelism of the model , And by optimizing the strategy of reading data sets in parallel , Put the model in IPU The throughput on the is brought into full play .
Improve on-chip memory utilization
By reducing the accuracy of some operations, compress the memory occupation on the chip , Save on-chip storage space , Thus, it supports the migration of optimizer state from off chip storage to on-chip storage , Reduce on-chip and off chip IO Interaction , And it can also improve the proportion of on-chip memory used by some operators , Improve the computational efficiency of operators .
The fusion collective operator
Multiple data generated in parallel collective Operators fuse into a single operator , While reducing synchronization overhead , It can also increase the utilization of bandwidth , Develop IPU Efficient computing performance .
Reduce unnecessary computing resources
Originally in evaluation Invalid reverse calculation is required in the process of , Currently, only the properties of the forward graph are calculated , save evalution Invalid calculation resource occupation in the process , Improve the whole evalution performance .
Hardware optimization
Bow-2000 Compare with M2000 It has a higher dominant frequency (1.4x), Greatly improve the computational efficiency .
Flying propeller And Graphcore The course of cooperation
Flying propeller We have been actively cooperating with hardware manufacturers to optimize user experience and performance .2020 year , Flying propeller Hand in hand 13 Hardware manufacturers initiated “ Hardware ecosystem ”,Graphcore That is, one of the initial members .2021 year , Baidu Flying propeller Implemented in the Graphcore IPU Comprehensive support for training and reasoning , And open source the relevant code . Both teams are in IPU-POD16&64 Data parallel and model parallel on , And in Bert-Base Intensive reading and throughput verification are carried out on the model, and good performance results are obtained .Graphcore Of Poplar SDK 2.3 Baidu Flying propeller The latest framework 2.3 Version has been fully integrated , The relevant code has been in Baidu Flying propeller Of GitHub Online for developers to get .
2022 year 5 month ,Graphcore stay WAVE SUMMIT 2022 At the deep learning developer summit, it was officially announced to join Baidu Flying propeller Launched the hardware ecosystem CO creation plan .Graphcore And baidu Flying propeller Based on this co creation plan, we will jointly develop technical solutions , Collaborative customization Flying propeller frame , Build model base and scenario base , With “IPU+ Flying propeller ” Empower industry , Drive industry AI Transformation and upgrading .
Conclusion
With the wide application and rapid development of artificial intelligence technology in various industries , The industry has entered the stage of algorithm and hardware collaborative innovation from their independent hardware computing power drive and algorithm innovation drive . This time MLPerf Joint submission of , It's Baidu. Flying propeller Create partners with hardware ecosystem Graphcore Innovative attempts of cooperation . future , Flying propeller Through the hardware ecosystem CO creation plan , With more hardware vendors , Accelerate the application of artificial intelligence , Push AI The realization process of industrial mass production .
MLPerf Introduce
MLPerf By AI Benchmark in the field of artificial intelligence initiated by world-renowned academic researchers and industry experts .MLPerf It aims to provide a fair 、 A practical benchmark platform , Show industry-leading AI The best performance of software and hardware system , The test results have been obtained AI General recognition in the field . Almost all mainstream hardware manufacturers and software service providers in the world will refer to MLPerf Build your own benchmark system based on the published results , To test the new AI Accelerating chip and deep learning framework in MLPerf Performance on the model .
Read more
Live broadcast announcement
7 month 6 Japan ( Wednesday )20:00, Flying propeller Chief architect Yu dianhai and Flying propeller Zeng Jinle, a senior R & D Engineer, will broadcast live , Uncover secrets for everyone GPU Under configuration , Baidu Flying propeller performance 「 World first 」 The key technology behind it .
Scan the qr code below , The background to reply 【 Study 】 Sign up , There are more gifts waiting for you in the live studio !
Focus on 【 Flying propeller PaddlePaddle】 official account
Get more technical content ~
This article is shared in Blog “ Flying propeller PaddlePaddle”(CSDN).
If there is any infringement , Please contact the [email protected] Delete .
Participation of this paper “OSC Source creation plan ”, You are welcome to join us , share .
边栏推荐
- Scrapy教程经典实战【新概念英语】
- Write it down once Net a new energy system thread surge analysis
- My "troublesome" subordinates after 00: not bad for money, against leaders, and resist overtime
- 2022-7-7 Leetcode 844.比较含退格的字符串
- JS slow motion animation principle teaching (super detail)
- [learning notes] segment tree selection
- Centso7 OpenSSL error Verify return code: 20 (unable to get local issuer certificate)
- Toraw and markraw
- toRaw和markRaw
- Ogre introduction
猜你喜欢
1. Deep copy 2. Call apply bind 3. For of in differences
flask session伪造之hctf admin
Deep understanding of array related problems in C language
MySQL error 28 and solution
干货|总结那些漏洞工具的联动使用
靠卖概念上市,认养一头牛能走多远?
2022-7-7 Leetcode 34.在排序数组中查找元素的第一个和最后一个位置
Enregistrement de la navigation et de la mise en service du robot ROS intérieur (expérience de sélection du rayon de dilatation)
【黑马早报】华为辟谣“军师”陈春花;恒驰5预售价17.9万元;周杰伦新专辑MV 3小时播放量破亿;法华寺回应万元月薪招人...
2022-7-6 Leetcode27.移除元素——太久没有做题了,为双指针如此狼狈的一天
随机推荐
MongoDB 分片总结
Talk about pseudo sharing
如何让join跑得更快?
JS function 返回多个值
社会责任·价值共创,中关村网络安全与信息化产业联盟对话网信企业家海泰方圆董事长姜海舟先生
MongoDB内部的存储原理
2022-7-6 使用SIGURG来接受外带数据,不知道为什么打印不出来
室内ROS机器人导航调试记录(膨胀半径的选取经验)
分布式事务解决方案
Ikvm of toolbox Net project new progress
Solve the cache breakdown problem
[learning notes] segment tree selection
Server to server (S2S) event (adjust)
《厌女:日本的女性嫌恶》摘录
Navicat运行sql文件导入数据不全或导入失败
LIS longest ascending subsequence problem (dynamic programming, greed + dichotomy)
Mongodb command summary
Fast development board pinctrl and GPIO subsystem experiment for itop-imx6ull - modify the device tree file
Mongodb replication (replica set) summary
Pcap learning notes II: pcap4j source code Notes