OpenXiangShan/GEM5
Oct 2025 – Mar 2026
5 Months active
Languages Used
C++Python
Technical Skills
Branch PredictionCPU ArchitecturePerformance OptimizationSystem SimulationC++ programmingdebugging
Cao Jiaming
PROFILE
Cao Jiaming
Contributed to the OpenXiangShan/GEM5 repository by designing and optimizing advanced branch prediction features in C++ and Python, focusing on MicroTAGE and BTBTAGE predictors. Over five months, delivered enhancements that improved prediction accuracy, configurability, and simulation observability, including refactoring history management, integrating new misprediction tracking, and aligning BTB entry handling with pipeline stages. Addressed debugging and maintainability by consolidating code paths, removing legacy logic, and introducing targeted bug fixes. Emphasized performance optimization and system simulation, enabling more reliable architectural exploration and analytics. Collaborated across multiple contributors, leveraging algorithm design and statistical analysis to support robust CPU microarchitecture modeling.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
18Total
Bugs
1
Commits
18
Features
7
Lines of code
3,433
Activity Months5
Your Network
42 peopleShared Repositories
28
Work History
March 2026
4 Commits • 2 Features
Mar 1, 2026Month: 2026-03 - GEM5 contributions focused on branch predictor enhancements and stability improvements. Key work delivered includes refactoring the MicroTAGE branch predictor for performance and clarity, updating history management and index calculations to improve prediction accuracy, and introducing a per-table configuration pathway for BTBTAGE (with a subsequent rollback to a stable fixed-per-set configuration to preserve reliability). These changes were complemented by targeted bug fixes to ensure consistent behavior across predictor configurations.
4 Commits • 2 Features
Mar 1, 2026Month: 2026-03 - GEM5 contributions focused on branch predictor enhancements and stability improvements. Key work delivered includes refactoring the MicroTAGE branch predictor for performance and clarity, updating history management and index calculations to improve prediction accuracy, and introducing a per-table configuration pathway for BTBTAGE (with a subsequent rollback to a stable fixed-per-set configuration to preserve reliability). These changes were complemented by targeted bug fixes to ensure consistent behavior across predictor configurations.
March 2026
January 2026
2 Commits • 1 Features
Jan 1, 2026January 2026 (OpenXiangShan/GEM5) focused on streamlining the branch prediction and BTB (branch target buffer) pipeline to improve simulation accuracy and maintainability. Core efforts were centered around consolidating predwrongSource handling for wrong-source predictions, aligning BTB entry processing with stage-based predictions, and removing legacy basetable logic to simplify the code path. Key results include a refactored BTB/prediction path that consolidates source handling, the introduction of wrong-prediction statistics for improved diagnostic visibility, and a marked reduction in dead/unused code by removing basetable logic from BTBTAGE and MBTB and related components.
January 2026
2 Commits • 1 Features
Jan 1, 2026January 2026 (OpenXiangShan/GEM5) focused on streamlining the branch prediction and BTB (branch target buffer) pipeline to improve simulation accuracy and maintainability. Core efforts were centered around consolidating predwrongSource handling for wrong-source predictions, aligning BTB entry processing with stage-based predictions, and removing legacy basetable logic to simplify the code path. Key results include a refactored BTB/prediction path that consolidates source handling, the introduction of wrong-prediction statistics for improved diagnostic visibility, and a marked reduction in dead/unused code by removing basetable logic from BTBTAGE and MBTB and related components.
December 2025
9 Commits • 2 Features
Dec 1, 2025December 2025: Delivered substantial branch predictor enhancements in GEM5 (OpenXiangShan) with focus on accuracy, configurability, and observability across ITTAGE/TAGE and UBTB/BTB. Key outcomes include ABTB configurability, S3 prediction handling, misprediction counters, and expanded commit statistics across ITTAGE/BTB components, supported by cleanup efforts. MBTB basetable alignment and integration progressed with fixed-target statistics and support for a choice MBTB basetable, boosting accuracy and analytics. Backend refactors and bug fixes across ABTB/MBTB/UBTB improved coherence and reduced debt. Overall business impact: more reliable performance modeling, faster tuning, and better decision support for architecture exploration. Technologies demonstrated: C++, hardware simulation internals, performance analytics, and collaborative git workflows across multiple contributors.
9 Commits • 2 Features
Dec 1, 2025December 2025: Delivered substantial branch predictor enhancements in GEM5 (OpenXiangShan) with focus on accuracy, configurability, and observability across ITTAGE/TAGE and UBTB/BTB. Key outcomes include ABTB configurability, S3 prediction handling, misprediction counters, and expanded commit statistics across ITTAGE/BTB components, supported by cleanup efforts. MBTB basetable alignment and integration progressed with fixed-target statistics and support for a choice MBTB basetable, boosting accuracy and analytics. Backend refactors and bug fixes across ABTB/MBTB/UBTB improved coherence and reduced debt. Overall business impact: more reliable performance modeling, faster tuning, and better decision support for architecture exploration. Technologies demonstrated: C++, hardware simulation internals, performance analytics, and collaborative git workflows across multiple contributors.
December 2025
November 2025
2 Commits • 1 Features
Nov 1, 2025November 2025 — OpenXiangShan/GEM5: Delivered internal branch prediction (ABTB) debugging enhancements and targeted UBTB/TAGE improvements to strengthen debugging capabilities, reliability, and microarchitectural performance. Implemented a dedicated ABTB debug flag, cleaned up legacy code for maintainability, and improved misprediction handling within the TAGE path. Addressed UBTB-related bugs to improve accuracy and measurement fidelity, enabling faster diagnosis and iteration for future optimizations.
November 2025
2 Commits • 1 Features
Nov 1, 2025November 2025 — OpenXiangShan/GEM5: Delivered internal branch prediction (ABTB) debugging enhancements and targeted UBTB/TAGE improvements to strengthen debugging capabilities, reliability, and microarchitectural performance. Implemented a dedicated ABTB debug flag, cleaned up legacy code for maintainability, and improved misprediction handling within the TAGE path. Addressed UBTB-related bugs to improve accuracy and measurement fidelity, enabling faster diagnosis and iteration for future optimizations.
October 2025
1 Commits • 1 Features
Oct 1, 2025OpenXiangShan/GEM5 (2025-10) focused on a targeted performance enhancement by integrating MicroTAGE into the S1 stage of the CPU pipeline. This work adds a MicroTAGE branch predictor to S1, updates predictor configuration, and refactors code for maintainability and easier integration with existing branch-prediction logic. The effort delivers a concrete architectural advancement for dynamic branch prediction, ready for broader evaluation and future optimization. Delivered commit: 340af13e8310dbbcdf9797b1d77ead2159321d2b ("Microtage on s1 perf (#567)").
1 Commits • 1 Features
Oct 1, 2025OpenXiangShan/GEM5 (2025-10) focused on a targeted performance enhancement by integrating MicroTAGE into the S1 stage of the CPU pipeline. This work adds a MicroTAGE branch predictor to S1, updates predictor configuration, and refactors code for maintainability and easier integration with existing branch-prediction logic. The effort delivers a concrete architectural advancement for dynamic branch prediction, ready for broader evaluation and future optimization. Delivered commit: 340af13e8310dbbcdf9797b1d77ead2159321d2b ("Microtage on s1 perf (#567)").
October 2025
Activity
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Quality Metrics
Correctness86.8%
Maintainability82.2%
Architecture83.4%
Performance81.2%
AI Usage32.2%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Branch PredictionC++ DevelopmentC++ developmentC++ programmingCPU ArchitecturePerformance OptimizationSystem Simulationalgorithm designbranch prediction algorithmsdebuggingmicroarchitectureperformance optimizationstatistical analysisstatistics trackingsystem design
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