Data Space Profiling for Network Application Bottleneck Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional profiling tools fail to effectively detect bottlenecks in modern multi-core, multi-threaded systems, particularly in the memory subsystem, and do not provide context-specific data and cost analysis, leading to inefficiencies in optimizing application performance.
Innovation Solution
A system and method for data space profiling that includes tagging apparatus, synchronization apparatus, and event agents to collect and analyze context-specific data, such as timestamps and extended addresses, to identify performance bottlenecks and optimize data movement between computing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If code instrumentation techniques are used to profile application code, then profiling data can be collected, but overhead is imposed on the original program code and program behavior may be altered
Solution Approach 1:
The patent introduces an intermediary profiling layer that sits between the application code and the execution environment. This layer collects profiling data through context switching and hardware support without requiring direct instrumentation of the original code, thereby maintaining program behavior while still enabling detailed performance analysis.
Solution Approach 2:
The patent replaces traditional software-based code instrumentation with a hybrid approach that leverages hardware support mechanisms. By using hardware-assisted context switching and dedicated profiling registers, the system reduces the software overhead and minimizes interference with the original program execution.
2Productivity
If traditional instruction-centric profiling tools are used, then profiling data can be obtained, but they fail to detect bottlenecks in the memory subsystem and data motion
Solution Approach 1:
The patent transitions from traditional instruction-centric profiling to a data-space profiling approach. By introducing a new dimension of analysis that tracks data addresses, memory accesses, and data motion patterns, the system enables detection of memory subsystem bottlenecks that were invisible to conventional profiling tools.
Solution Approach 2:
The patent changes the fundamental parameters being profiled from instruction-level metrics to data-space metrics. By tracking data addresses, memory hierarchy performance, and data motion characteristics, the system provides new insights into performance bottlenecks that traditional parameter sets could not reveal.
3Productivity
If multi-threaded cores are used to hide data latency, then throughput can be improved, but accurate identification and characterization of data motion becomes critical for scalability
Solution Approach 1:
The patent creates a universal profiling framework that handles both traditional instruction-level analysis and new data-space analysis through a unified architecture. This multi-functional approach allows the same profiling infrastructure to support single-threaded and multi-threaded workloads while providing consistent data motion characterization across different execution models.
Data Source
AI summary
A system and method for profiling a network application may provide for operating on context-specific data and costs. The system may include an apparatus for associating local extended address elements with a message sent from a first computing system to a second computing system across a network. The second computing system may store the received information as remote extended address information and may store its own local extended address information. An event agent may capture values of local and/or remote extended address elements in response to detecting the message or another system event and may associate the extended address elements with the message or system event in an event set accessible by a data space profiler. The extended address information may include time stamps. An event agent may determine network latency dependent on time stamps of messages and may generate an event if the latency exceeds a predetermined threshold.