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公开(公告)号：US20240289818A1
公开(公告)日：2024-08-29
申请号：US18332118
申请日：2023-06-09
发明人： Jesus CAMACHO RODRIGUEZ , Kwanghyun PARK , Fotios PSALLIDAS , Xiaoyong ZHU , Jinghui MO , Rathijit SEN , Matteo INTERLANDI , Yuanyuan TIAN , Rui LIU , Konstantinos KARANASOS
IPC分类号： G06Q30/0201 , G06N20/00
CPC分类号： G06Q30/0201 , G06N20/00
摘要： The described technology provides a method including receiving a new feature definition; the new feature definition specifying parameters of the feature, comparing the new feature definition with a plurality of computed feature definitions stored in a feature store, and in response to determining that the new feature definition is at least partially contained in a matched feature definition of the plurality of computed feature definitions, generating an alternative feature definition based on the new feature definition and the matched feature definitions, and selecting an execution alternative from an execution of a PIT join using the alternative feature definition and an execution of a PIT join using the new feature definition.
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公开(公告)号：US20210096915A1
公开(公告)日：2021-04-01
申请号：US16697960
申请日：2019-11-27
发明人： Hiren Shantilal PATEL , Shi QIAO , Alekh JINDAL , Malay Kumar BAG , Rathijit SEN , Carlo Aldo CURINO
IPC分类号： G06F9/50 , G06F9/48 , G06N5/04 , G06N20/00 , G06F16/2453
摘要： A serverless query processing system receives a query and determines whether the query is a recurring query or a non-recurring query. The system may predict, in response to determining that the query is the recurring query, a peak resource requirement during an execution of the query. The system may compute, in response to determining that the query is the non-recurring query, a tight resource requirement corresponding to an amount of resources that satisfy a performance requirement over the execution of the query, where the tight resource requirement is less than the peak resource requirement. The system allocates resources to the query based on an applicable one of the peak resource requirement or the tight resource requirement. The system then starts the execution of the query using the resources.
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公开(公告)号：US20240126604A1
公开(公告)日：2024-04-18
申请号：US18161679
申请日：2023-01-30
发明人： Rathijit SEN , Matteo INTERLANDI , Jiashen CAO
IPC分类号： G06F9/50
CPC分类号： G06F9/5016 , G06F9/505
摘要： A system provisioning resources of a processing unit. The system predicts a performance impact on a workload attributable to a performance constraint of the processing unit for the workload according to a resource model, wherein the workload includes a query and the resource model characterizes attainable compute bandwidth, attainable memory bandwidth, and arithmetic intensity based on peak compute bandwidth and peak memory bandwidth of the processing unit. The system determines a resource allocation of the processing unit, based on the predicted performance impact and instructs the processing unit to allocate the resources for processing the workload based on the determined resource allocation.
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公开(公告)号：US20220100763A1
公开(公告)日：2022-03-31
申请号：US17060053
申请日：2020-09-30
发明人： Rathijit SEN , Alekh JINDAL , Anish Yatin PIMPLEY , Shuo LI , Anubha SRIVASTAVA , Vishal Lalchand ROHRA , Yi ZHU , Hiren Shantilal PATEL , Shi QIAO , Marc Todd FRIEDMAN , Clemens Alden SZYPERSKI
IPC分类号： G06F16/2453 , G06N20/00
摘要： Solutions for optimizing job runtimes via prediction-based token allocation includes receiving training data comprising historical run data, the historical run data comprising job characteristics, runtime results, and a token count for each of a plurality of prior jobs, and the job characteristics comprising an intermediate representation and job graph data; based at least on the training data, training a token estimator, the token estimator comprising a machine learning (ML) model; receiving job characteristics for a user-submitted job; based at least on the received job characteristics, generating, with the token estimator, token prediction data for the user-submitted job; selecting a token count for the user-submitted job, based at least on the token prediction data; identifying the selected token count to an execution environment; and executing, with the execution environment, the user-submitted job in accordance with the selected token count.
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公开(公告)号：US20210089532A1
公开(公告)日：2021-03-25
申请号：US16581905
申请日：2019-09-25
发明人： Hiren S. PATEL , Rathijit SEN , Zhicheng YIN , Shi QIAO , Abhishek ROY , Alekh JINDAL , Subramaniam Venkatraman KRISHNAN , Carlo Aldo CURINO
IPC分类号： G06F16/2453
摘要： The cloud-based query workload optimization system disclosed herein the cloud-based query workloads optimization system receives query logs from various query engines to a cloud data service, extracts various query entities from the query logs, parses query entities to generate a set of common workload features, generates intermediate representations of the query workloads, wherein the intermediate representations are agnostic to the language of the plurality of the queries, identifies a plurality of workload patterns based on the intermediate representations of the query workloads, categorizes the workloads in one or more workload type categories based on the workload patterns and the workload features, and selects an optimization scheme based on the category of workload pattern.
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公开(公告)号：US20230376800A1
公开(公告)日：2023-11-23
申请号：US17746245
申请日：2022-05-17
发明人： Yiwen ZHU , Rathijit SEN , Robert McArn HORTON , John Mark AGOSTA
CPC分类号： G06N5/04 , G06F9/4843 , G06N5/022
摘要： Methods, systems and computer program products are provided for predicting runtime variation in big data analytics. Runtime probability distributions may be predicted for proposed computing jobs. A predictor may classify proposed computing jobs based on multiple runtime probability distributions that represent multiple clusters of runtime probability distributions for multiple executed recurring computing job groups. Proposed computing jobs may be classified as delta-normalized runtime probability distributions and/or a ratio-normalized runtime probability distributions. Sources of runtime variation may be identified with a quantitative contribution to predicted runtime variation. A runtime probability distribution editor may indicate modifications to sources of runtime variation in a proposed computing job and/or predict reductions in predicted runtime variation provided by modifications to a proposed computing job.
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公开(公告)号：US20230244662A1
公开(公告)日：2023-08-03
申请号：US17587952
申请日：2022-01-28
发明人： Matteo INTERLANDI , Konstantinos KARANASOS , Dong HE , Dalitso Hansini BANDA , Jesus CAMACHO RODRIGUEZ , Rathijit SEN , Supun Chathurang NAKANDALA
IPC分类号： G06F16/2453 , G06F16/2458 , G06N3/04
CPC分类号： G06F16/24542 , G06F16/2458 , G06N3/04
摘要： Example aspects include techniques for query processing over deep neural network runtimes. These techniques may include receiving a query including one or more query operators and determining a query representation based on the one or more query operators. In addition, the techniques may include determining a neural network program based on the query representation, the neural network program including one or more neural network operators for performing the query in a neural network runtime, generating a neural network data structure based on a dataset associated with the query, and executing the neural network program in the neural network runtime over the neural network data structure to generate a query result.
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公开(公告)号：US20220413914A1
公开(公告)日：2022-12-29
申请号：US17894628
申请日：2022-08-24
发明人： Hiren Shantilal PATEL , Shi QIAO , Alekh JINDAL , Malay Kumar BAG , Rathijit SEN , Carlo Aldo CURINO
IPC分类号： G06F9/50 , G06F9/48 , G06N20/00 , G06F16/2453 , G06N5/04
摘要： A serverless query processing system receives a query and determines whether the query is a recurring query or a non-recurring query. The system may predict, in response to determining that the query is the recurring query, a peak resource requirement during an execution of the query. The system may compute, in response to determining that the query is the non-recurring query, a tight resource requirement corresponding to an amount of resources that satisfy a performance requirement over the execution of the query, where the tight resource requirement is less than the peak resource requirement. The system allocates resources to the query based on an applicable one of the peak resource requirement or the tight resource requirement. The system then starts the execution of the query using the resources.
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公开(公告)号：US20240311380A1
公开(公告)日：2024-09-19
申请号：US18465764
申请日：2023-09-12
发明人： Matteo INTERLANDI , Wei CUI , Qianxi ZHANG , Peng CHENG , Rathijit SEN
IPC分类号： G06F16/245 , G06F16/2453
CPC分类号： G06F16/24569 , G06F16/24542
摘要： Query processing systems and methods are disclosed herein. In an example system, query information is received over a network for processing a query. A first processing architecture loads a set of data associated with the query into a shared memory. A second processing architecture accesses the set of data from the shared memory. In one example, the first and second processing architectures and the shared memory are integrated in a hardware chip (e.g., a chiplet containing several processor architectures, such as CPU and a graphics processing unit (GPU)). The query is processed based on the set of data accessed from the shared memory using the second processing architecture to generate a query result. The query result is provided over the network. In this manner, a computing device may execute a query based on different processing systems contained therein.
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公开(公告)号：US20210124739A1
公开(公告)日：2021-04-29
申请号：US16990506
申请日：2020-08-11
发明人： Konstantinos KARANASOS , Matteo INTERLANDI , Fotios PSALLIDAS , Rathijit SEN , Kwanghyun PARK , Ivan POPIVANOV , Subramaniam VENKATRAMAN KRISHNAN , Markus WEIMER , Yuan YU , Raghunath RAMAKRISHNAN , Carlo Aldo CURINO , Doris Suiyi XIN , Karla Jean SAUR
IPC分类号： G06F16/2458 , G06N5/04 , G06N20/00 , G06F16/28
摘要： The description relates to executing an inference query relative to a database management system, such as a relational database management system. In one example a trained machine learning model can be stored within the database management system. An inference query can be received that applies the trained machine learning model on data local to the database management system. Analysis can be performed on the inference query and the trained machine learning model to generate a unified intermediate representation of the inference query and the trained model. Cross optimization can be performed on the unified intermediate representation. Based upon the cross-optimization, a first portion of the unified intermediate representation to be executed by a database engine of the database management system can be determined, and, a second portion of the unified intermediate representation to be executed by a machine learning runtime can be determined.
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