Modular Analysis Framework for Hardware Simulation
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Solution Overview
Problem
Current methods struggle to perform accurate application-level analysis of software on emerging hardware systems, leading to errors in designing future hardware due to segregation of application performance expertise and hardware simulation expertise, and the lack of flexible tools for dynamic analysis in simulation environments.
Innovation Solution
A computer system with a hardware simulator that executes software on simulated hardware, intercepts interactions, and processes data through a multi-level framework with interchangeable analysis modules, enabling detailed application-level performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If workload analysis tools are used in isolation from hardware simulation tools, then tool complexity is reduced and ease of operation is improved, but measurement precision and reliability of performance analysis deteriorate due to inability to perform application-level analysis of emerging hardware
Solution Approach 1:
The patent merges workload analysis tools with hardware simulation tools into a unified integrated environment. This integration allows software engineers and hardware engineers to collaboratively analyze software application performance on emerging hardware platforms simultaneously, enabling precise measurement of performance metrics while maintaining ease of operation through a unified interface that combines the capabilities of both tool types.
Solution Approach 2:
The integrated environment provides multi-functional capabilities by combining workload analysis functions with hardware simulation functions in a single system. This universal platform can perform both traditional workload analysis and emerging hardware performance simulation, eliminating the need for separate tools while maintaining operational simplicity through a unified toolset that serves multiple purposes.
2Productivity
If existing workload analysis tools are extended to new applications, then development time is reduced and productivity is improved, but device complexity increases requiring engineers to understand source code and tool structure
Solution Approach 1:
The patent segments the analysis system into modular components including workload analysis modules, hardware simulation modules, and integration layers. This segmentation allows engineers to use pre-built modular components for rapid analysis feedback while reducing the need to understand the entire system's source code and structure, as each module can be independently configured and understood.
Solution Approach 2:
The patent introduces an intermediary integration layer that connects workload analysis tools with hardware simulation tools. This intermediary handles the complexity of interfacing between different tool types, allowing engineers to achieve high productivity through a simplified interface while the underlying complexity is managed by the intermediary translation and coordination layer.
3Adaptability or versatility
If new tools are developed instead of extending existing tools, then adaptability to new applications is improved, but loss of time occurs due to duplication of work and slowed analysis feedback
Solution Approach 1:
The patent creates a universal integrated environment that can adapt to different hardware architectures through configurable hardware simulation modules while reusing existing workload analysis tool components. This approach provides the adaptability needed for emerging hardware platforms without requiring complete new tool development, thereby avoiding time loss from duplicating work that can be achieved through configuration rather than development.
Solution Approach 2:
The patent performs preliminary integration work by pre-building the framework that connects workload analysis tools with hardware simulation capabilities. This preliminary action establishes a reusable infrastructure that can be quickly adapted to different hardware architectures without requiring time-consuming new tool development for each application, thus reducing time loss while maintaining adaptability.
4Productivity
If extrapolation methods are used to predict future hardware performance, then analysis time is reduced and productivity is improved, but measurement precision deteriorates due to inherent errors in extrapolation
Solution Approach 1:
The patent performs preliminary performance analysis directly on the emerging hardware platform through integrated simulation before actual hardware fabrication. This preliminary action provides accurate performance data specific to the target hardware architecture, eliminating the need for error-prone extrapolation methods while maintaining fast analysis throughput through the efficient integrated environment.
Solution Approach 2:
The patent creates a virtual copy of the emerging hardware platform through hardware simulation that accurately replicates the target architecture's behavior. This virtual copy allows for precise performance measurement that reflects actual hardware characteristics rather than extrapolated estimates, while maintaining the speed benefits of software-based analysis through the integrated tool environment.
Data Source
AI summary
An object-oriented software analysis framework is provided for enabling software engineers and hardware engineers to gain insight into the behavior of software applications on emerging hardware platforms even before the hardware is fabricated. In this analysis framework, simulation data containing instruction, address and/or hardware register information is sent to interchangeable and parameterizable analyzer and profiler modules that decode the data and perform analysis of the data according to each module's respective analysis function. This detailed analysis is performed by constructing a tree of such modules through which the data travels and is classified and analyzed or filtered at each level of the tree. Each node of the tree is represented by an analyzer or a profiler module that performs sub-analysis based on the analysis performed by its parent such that at the end of a hardware simulation, each node, starting at the root, recursively calls on its children to dump their analysis, resulting in a categorized performance report.