Microsoft Technology Licensing, LLC

Huawei Technologies Co., Limited

North China Electric Power University

Chen Wu

Neelakantan Sundaresan

Roshanak Zilouchian Moghaddam

Paul Sean Harrington

Spandan Garg

Alexey Svyatkovskiy

Colin Bruce Clement

Dawn Drain

Yifan Lin

Bo Zeng

Yunxiao Zhang

Xiaoqiang Dan

A computer implemented method includes accessing performance trace data for executed code of multiple services. Symbols corresponding to functions of the executed code are identified. First sequences of functions from the identified symbols are identified and a first performance threshold for each identified first sequence of functions is computed. The method includes receiving an incoming performance trace, detecting second sequences of functions from the incoming performance trace, identifying second sequences equivalent to the first sequences, and comparing performance of the identified second sequences to the first performance threshold for each of the equivalent first sequences to identify second sequences as comprising a performance bottleneck.

System and method for identifying performance bottlenecks

The present disclosure discloses a method for performing multi-stage multi-level cooperative operation on a park integrated energy system containing a mineral industry user. The method includes: constructing a short-time scale dynamic pricing model, including an upper-layer CMIES operation optimization model and a lower-layer user demand response model; solving the short-time scale dynamic pricing model to obtain day-ahead and intraday scheduling plans and a next-day electricity price; and based on the day-ahead and intraday scheduling plans and the next-day electricity price, computing a strategy transfer probability distribution of each subject within a preset deadline, and simulating a decision-making process by a Monte Carlo method until each subject reaches a correlated equilibrium state to obtain a pricing solution of CMIES within the preset deadline. According to the present disclosure, the energy utilization efficiency of the system can be improved, and the operation cost can be reduced.

Method for performing multi-stage multi-level cooperative operation on park integrated energy system containing mineral industry user

An automated system for detecting performance bugs in a program and for providing code recommendations to improve the performance of the program generates a code recommendation table from performance-related pull requests. The performance-related pull requests are identified in part from a classifier trained on semi-supervised data. A code recommendation table is generated from performance-related pull requests and is searched for similarly-improved code based on a set of difference features that includes structural and performance features of the before-code of a pull request that is not in the after-code.

Performance bug detection and code recommendation

An automated system for translating source code written in one programming language into a different programming language utilizes a neural transformer with attention trained on semi-supervised data. The model is jointly pre-trained with a masked language model objective and an autoregressive objective on a large unsupervised source code corpus to learn to comprehend the syntactic structure and semantics of source code. The pre-trained model is then fine-tuned with a token-type prediction objective and an autoregressive objective on supervised translation tasks and data augmented tasks to learn to translate source code from one programming language into a different programming language.

Semi-supervised translation of source code programs using neural transformers

An SIMD instruction generation and processing method and a related device are provided. The method may include: obtaining a length of each loop dimension of a first tensor formula; selecting, from a plurality of groups of information about a first SIMD instruction model based on the length of each loop dimension of a first tensor formula, information about a second SIMD instruction model matching the first tensor formula; generating, based on a length of at least one loop dimension of the first tensor formula and the second SIMD instruction model, a first SIMD instruction obtained after the first tensor formula is converted. The information about a second SIMD instruction model is selected from the plurality of groups of information about a first SIMD instruction model based on the length of each loop dimension of the tensor formula.

Single instruction multiple data SIMD instruction generation and processing method and related device

Growing community of inventors

Shanghai, China

Chen Wu