GGID-Correlated Hardware Tracing for Distributed Application Profiling
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Solution Overview
Problem
Existing performance analysis and debug capabilities for distributed applications, especially those using heterogeneous machines interconnected via computer networks with different latencies and capacities, are inadequate, particularly in multitenant deployments where processing resources are virtualized and leased to multiple users.
Innovation Solution
A method and compute platform that utilize a global group ID (GGID) to map and correlate telemetry data across distributed compute nodes, align data based on common timestamps, and account for differences in compute capability, enabling holistic performance profiling and debug across multiple nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If function-based profiling is used for single-node applications, then performance hotspots can be easily identified, but this approach becomes significantly more complicated for distributed applications across multiple heterogeneous nodes
Solution Approach 1:
The system segments the distributed application tracing into node-specific components (local tracing agents on each compute node) and a central aggregation component. Each node independently collects telemetry data locally, then the system aggregates these segmented data streams with timestamp alignment to reconstruct end-to-end application performance across the distributed system.
Solution Approach 2:
The patent introduces an intermediary tracing system that sits between the distributed application components and the analysis tools. This intermediary collects telemetry data from multiple heterogeneous nodes, aligns timestamps, and presents unified performance data, thereby simplifying the complexity for end users while maintaining measurement precision.
2Productivity
If multiple servers are used to execute a single distributed application, then greater compute performance is achieved, but performance analysis and debug capabilities become inadequate
Solution Approach 1:
The system merges telemetry data from multiple distributed servers into a unified performance view. By combining node identifiers, process identifiers, and aligned timestamp data from all servers participating in the distributed application, the system reconstructs complete performance information that would be lost if each node were analyzed in isolation.
Solution Approach 2:
The tracing system is designed to be universal across heterogeneous computing platforms. It can collect and correlate performance data from any compute node regardless of its specific hardware configuration, operating system, or role in the distributed application, thereby maintaining full performance visibility across diverse infrastructure.
3Adaptability or versatility
If processing resources are virtualized and leased to multiple users in multitenant deployments, then resource utilization efficiency increases, but tracing and debugging become more complex
Solution Approach 1:
The tracing system implements local quality by capturing process-specific telemetry data at each virtualized compute node. Each virtual machine or container is traced with its own process identifier and node identifier, allowing the system to distinguish and analyze performance characteristics of individual tenant workloads running on shared physical infrastructure without interference from other tenants.
Data Source
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AI summary
Methods and apparatus for scale out hardware-assisted tracing schemes for distributed and scale-out applications. In connection with execution of one or more applications using a distributed processing environment including multiple compute nodes, telemetry and tracing data are obtained using hardware-based logic on the compute nodes. Processes associated with applications are identified, as well as the compute nodes on which instances of the processes are executed. Process instances are associated with process application space identifiers (PASIDs), while processes used for an application are associating with a global group identifier (GGID) that serves as an application ID. The PASIDs and GGIDs are used to store telemetry and/or tracing data on the compute nodes and/or forward such data to a tracing server in a manner that enables telemetry and/or tracing data to be aggregated on an application basis.