Scalable prediction by partial match (PPM) and its application to route prediction
نویسندگان
چکیده
منابع مشابه
Neuro-PPM Branch Prediction
Historically, Markovian predictors have been very successful in predicting branch outcomes. In this work we propose a hybrid scheme that employs two Prediction by Partial Matching (PPM) Markovian predictors, one that predicts based on local branch histories and one based on global branch histories. The two independent predictions are combined using a neural network. On the CBP-2 traces the prop...
متن کاملconstruction and validation of translation metacognitive strategy questionnaire and its application to translation quality
like any other learning activity, translation is a problem solving activity which involves executing parallel cognitive processes. the ability to think about these higher processes, plan, organize, monitor and evaluate the most influential executive cognitive processes is what flavell (1975) called “metacognition” which encompasses raising awareness of mental processes as well as using effectiv...
Ensemble Prediction by Partial Matching
Prediction by Partial Matching (PPM) is a lossless compression algorithm which consistently performs well on text compression benchmarks. This paper introduces a new PPM implementation called PPM-Ens which uses unbounded context lengths and ensemble voting to combine multiple contexts. The algorithm is evaluated on the Calgary corpus. The results indicate that combining multiple contexts leads ...
متن کاملClassification and its application to drug-target interaction prediction
Classification is one of the most popular and widely used supervised learning tasks, which categorizes objects into predefined classes based on known knowledge. Classification has been an important research topic in machine learning and data mining. Different classification methods have been proposed and applied to deal with various real-world problems. Unlike unsupervised learning such as clus...
متن کاملDynamic Data Dependence Tracking and its Application to Branch Prediction
To continue to improve processor performance, microarchitects seek to increase the effective instruction level parallelism (ILP) that can be exploited in applications. A fundamental limit to improving ILP is data dependences among instructions. If data dependence information is available at run-time, there are many uses to improve ILP. Prior published examples include decoupled branch execution...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Informatics
سال: 2018
ISSN: 2196-0089
DOI: 10.1186/s40535-018-0051-z