mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2026-05-05 07:11:39 +00:00
57d14d22bc
* refactor: move legacy code to archive/ directory - Moved ktransformers, csrc, third_party, merge_tensors to archive/ - Moved build scripts and configurations to archive/ - Kept kt-kernel, KT-SFT, doc, and README files in root - Preserved complete git history for all moved files * refactor: restructure repository to focus on kt-kernel and KT-SFT modules * fix README * fix README * fix README * fix README * docs: add performance benchmarks to kt-kernel section Add comprehensive performance data for kt-kernel to match KT-SFT's presentation: - AMX kernel optimization: 21.3 TFLOPS (3.9× faster than PyTorch) - Prefill phase: up to 20× speedup vs baseline - Decode phase: up to 4× speedup - NUMA optimization: up to 63% throughput improvement - Multi-GPU (8×L20): 227.85 tokens/s total throughput with DeepSeek-R1 FP8 Source: https://lmsys.org/blog/2025-10-22-KTransformers/ This provides users with concrete performance metrics for both core modules, making it easier to understand the capabilities of each component. * refactor: improve kt-kernel performance data with specific hardware and models Replace generic performance descriptions with concrete benchmarks: - Specify exact hardware: 8×L20 GPU + Xeon Gold 6454S, Single/Dual-socket Xeon + AMX - Include specific models: DeepSeek-R1-0528 (FP8), DeepSeek-V3 (671B) - Show detailed metrics: total throughput, output throughput, concurrency details - Match KT-SFT presentation style for consistency This provides users with actionable performance data they can use to evaluate hardware requirements and expected performance for their use cases. * fix README * docs: clean up performance table and improve formatting * add pic for README * refactor: simplify .gitmodules and backup legacy submodules - Remove 7 legacy submodules from root .gitmodules (archive/third_party/*) - Keep only 2 active submodules for kt-kernel (llama.cpp, pybind11) - Backup complete .gitmodules to archive/.gitmodules - Add documentation in archive/README.md for researchers who need legacy submodules This reduces initial clone size by ~500MB and avoids downloading unused dependencies. * refactor: move doc/ back to root directory Keep documentation in root for easier access and maintenance. * refactor: consolidate all images to doc/assets/ - Move kt-kernel/assets/heterogeneous_computing.png to doc/assets/ - Remove KT-SFT/assets/ (images already in doc/assets/) - Update KT-SFT/README.md image references to ../doc/assets/ - Eliminates ~7.9MB image duplication - Centralizes all documentation assets in one location * fix pic path for README
46 lines
861 B
INI
46 lines
861 B
INI
[loggers]
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keys=root,uvicorn,uvicornError,uvicornAccess
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[handlers]
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keys=consoleHandler,fileHandler
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[formatters]
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keys=detailedFormatter
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[logger_root]
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level=INFO
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handlers=consoleHandler
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[logger_uvicorn]
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level=INFO
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handlers=consoleHandler,fileHandler
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qualname=uvicorn
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propagate=0
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[logger_uvicornError]
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level=ERROR
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handlers=consoleHandler,fileHandler
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qualname=uvicorn.error
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propagate=0
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[logger_uvicornAccess]
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level=INFO
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handlers=consoleHandler,fileHandler
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qualname=uvicorn.access
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propagate=0
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[handler_consoleHandler]
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class=StreamHandler
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level=INFO
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formatter=detailedFormatter
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args=(sys.stdout,)
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[handler_fileHandler]
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class=logging.FileHandler
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level=INFO
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formatter=detailedFormatter
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args=('uvicorn_logs.log', 'a')
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[formatter_detailedFormatter]
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format=%(asctime)s - %(name)s - %(levelname)s - [%(filename)s:%(lineno)d] - %(message)s
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datefmt=%Y-%m-%d %H:%M:%S
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