Version 1.3.0

[tgrogers]

Accel-Sim Framework Release Notes

Major Features and Improvements

Trace Generation and Processing

• Updated tracer tool to use NVBit 1.7, improving compatibility and performance [8d0785d]
• Added support for compressed (xz) trace file generation by default [b5f038e]
• Improved trace parser performance and memory usage [4be9303, 08b9e9c]
• Replaced std::cin with a custom PipeReader class for improved trace parsing [16b55f1]
• Supports execution from compressed traces, saving runtime disk space by ~20-30x.

Multi-Stream Support

• Added per-stream statistics collection and reporting [f783a4c]
• Implemented passing of CUDA stream IDs from Accel-Sim to GPGPU-Sim for accurate multi-stream simulation [f783a4c]

Hardware Correlation

• Updated correlation scripts to support parsing data from newer NVIDIA profiling tools [56c5950]
• Added support for correlating with NVIDIA H100 GPU data [3a8112f]
• Improved handling of hardware data collection for various GPU architectures [56c5950, 3a8112f]

Configuration and Benchmark Management

• Updated CUTLASS benchmark naming and configuration [8253fd6]
• Implemented truncation of excessively long simulation names to improve file system compatibility [76dfd0b]

CI/CD and Testing

• Updated CI workflows to use the latest hardware data and improve correlation testing [56c5950, 01feb3c]
• Implemented automated code formatting checks in the CI pipeline [4a90ea7]

Bug Fixes and Optimizations

• Fixed issues with running hardware traces, including proper handling of kernel limits [49fe436]
• Resolved compatibility issues with newer CUDA versions and GPU architectures [8d0785d]
• Improved error handling and reporting in various scripts [3a8112f, 49fe436]

Documentation and Usability

• Updated README files and documentation to reflect recent changes [b5f038e]
• Improved error messages and user guidance for environment setup [8d0785d]

Acknowledgments

This release represents the collective effort of numerous contributors, including researchers and developers from various institutions. Their dedication has significantly advanced the capabilities of GPU architectural simulation.

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This discussion was created from the release Version 1.3.0.