Abstract: The present disclosure provides a light detection and ranging (LIDAR) system, which comprises: a distance measuring unit configured to emit a plurality of first pulses towards an object located in a field of view (FOV), wherein the object is associated with one or more markers; and a detector configured to receive at least one second pulse from the one or more markers of the object, wherein each of the at least one second pulse indicates object information identifying the object.

Abstract: Adaptive data collections may include various type of data arrays, sets, bags, maps, and other data structures. A simple interface for each adaptive collection may provide access via a unified API to adaptive implementations of the collection. A single adaptive data collection may include multiple, different adaptive implementations. A system configured to implement adaptive data collections may include the ability to adaptively select between various implementations, either manually or automatically, and to map a given workload to differing hardware configurations. Additionally, hardware resource needs of different configurations may be predicted from a small number of workload measurements. Adaptive data collections may provide language interoperability, such as by leveraging runtime compilation to build adaptive data collections and to compile and optimize implementation code and user code together.

Abstract: Adaptive data collections may include various type of data arrays, sets, bags, maps, and other data structures. A simple interface for each adaptive collection may provide access via a unified API to adaptive implementations of the collection. A single adaptive data collection may include multiple, different adaptive implementations. A system configured to implement adaptive data collections may include the ability to adaptively select between various implementations, either manually or automatically, and to map a given workload to differing hardware configurations. Additionally, hardware resource needs of different configurations may be predicted from a small number of workload measurements. Adaptive data collections may provide language interoperability, such as by leveraging runtime compilation to build adaptive data collections and to compile and optimize implementation code and user code together.

Abstract: Techniques are described herein for asynchronous execution of queries on statically replicated graph data. In an embodiment, a graph is partitioned among a plurality of computers executing the graph querying engine. One or more high-degree vertices of the graph are each replicated in each graph partition. The partitions, including the replicated high-degree vertices, are loaded in memory of the plurality of computers. To execute a query, a query plan is generated based on the query. The query plan specifies a plurality of operators and an order for the plurality of operators. The order is such that if an operator requires data generated by another operator, then the other operator is ordered before the operator in the query plan. Replicated copies of a vertex is visited if matches made by subsequent operator(s) are limited by data unique to the replicated vertices.

Abstract: Adaptive data collections may include various type of data arrays, sets, bags, maps, and other data structures. A simple interface for each adaptive collection may provide access via a unified API to adaptive implementations of the collection. A single adaptive data collection may include multiple, different adaptive implementations. A system configured to implement adaptive data collections may include the ability to adaptively select between various implementations, either manually or automatically, and to map a given workload to differing hardware configurations. Additionally, hardware resource needs of different configurations may be predicted from a small number of workload measurements. Adaptive data collections may provide language interoperability, such as by leveraging runtime compilation to build adaptive data collections and to compile and optimize implementation code and user code together.

Abstract: Adaptive data collections may include various type of data arrays, sets, bags, maps, and other data structures. A simple interface for each adaptive collection may provide access via a unified API to adaptive implementations of the collection. A single adaptive data collection may include multiple, different adaptive implementations. A system configured to implement adaptive data collections may include the ability to adaptively select between various implementations, either manually or automatically, and to map a given workload to differing hardware configurations. Additionally, hardware resource needs of different configurations may be predicted from a small number of workload measurements. Adaptive data collections may provide language interoperability, such as by leveraging runtime compilation to build adaptive data collections and to compile and optimize implementation code and user code together.

Abstract: Adaptive data collections may include various type of data arrays, sets, bags, maps, and other data structures. A simple interface for each adaptive collection may provide access via a unified API to adaptive implementations of the collection. A single adaptive data collection may include multiple, different adaptive implementations. A system configured to implement adaptive data collections may include the ability to adaptively select between various implementations, either manually or automatically, and to map a given workload to differing hardware configurations. Additionally, hardware resource needs of different configurations may be predicted from a small number of workload measurements. Adaptive data collections may provide language interoperability, such as by leveraging runtime compilation to build adaptive data collections and to compile and optimize implementation code and user code together.

Abstract: Techniques are described herein for asynchronous execution of queries on statically replicated graph data. In an embodiment, a graph is partitioned among a plurality of computers executing the graph querying engine. One or more high-degree vertices of the graph are each replicated in each graph partition. The partitions, including the replicated high-degree vertices, are loaded in memory of the plurality of computers. To execute a query, a query plan is generated based on the query. The query plan specifies a plurality of operators and an order for the plurality of operators. The order is such that if an operator requires data generated by another operator, then the other operator is ordered before the operator in the query plan. Replicated copies of a vertex is visited if matches made by subsequent operator(s) are limited by data unique to the replicated vertices.