Oracle International Corporation

Daniel J Goodman

Timothy Lawrence Harris

Jean-Pierre Lozi

Iraklis Psaroudakis

Matthias Grimmer

Stefan Kaestle

Roni T Haecki

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. Adaptive data collections may also provide language-independent such that implementation code may be written once and subsequently used from multiple programming languages.

Language interoperable runtime adaptable data collections

A system configured to implement Comprehensive Contention-Based Thread Allocation and Placement, may generate a description of a workload from multiple profiling runs and may combine this workload description with a description of the machine's hardware to model the workload's performance over alternative thread placements. For instance, the system may generate a machine description based on executing stress applications and machine performance counters monitoring various performance indicators during execution of a synthetic workload. Such a system may also generate a workload description based on profiling sessions and the performance counters. Additionally, behavior of a workload with a proposed thread placement may be modeled based on the machine description and workload description and a prediction of the workload's resource demands and/or performance may be generated.

Comprehensive contention-based thread allocation and placement

A system configured to implement detection, modeling and application of memory bandwidth patterns may predict performance of multi-threaded applications with different thread placements. Additionally, such a system may model bandwidth requirements of an application based on placement of the application's threads and may generate a bandwidth signature by sampling performance counters while executing the application using specific thread placement and determining values for multiple classes of bandwidth, such as static, local, per-thread and interleaved. Performance counters may information such as elapsed time, number of instructions executed, and/or the volume of data read or written to each memory bank. A bandwidth signature may be used to apply bandwidth requirements to differing thread placements within various types of systems, such as performance prediction systems, data structure libraries, as well as debugging and development systems.

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Bagillt, United Kingdom

Daniel J Goodman