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## Summary Introduces a CLI tool to load, index, and align benchmark JSON results from both backends. It displays a side-by-side comparison table showing latency (ms), throughput (tokens/s), and the percentage speedup/slowdown.
## Summary execution wrapper for Python runner Adds a boilerplate compatibility script to handle safe system exits and execution routing for python benchmark.
## Summary
Introduces the primary Python benchmark runner, measuring model
metadata, data throughput, forward latency, training-step latency, and
autoregressive generation. Includes utility functions for dynamic module
loading, timing, and percentile calculation.
## Model BenchmarkingLatency Profiling:
Tracks forward pass, training step, and autoregressive generation
latencies.Throughput Tracking: Measures tokenizer processing speeds and
data throughput.Resource Monitoring: Captures model metadata and system
memory footprints during runs.
## Math UtilitiesDynamic Loading:
Implements safe runtime module loading via importlib to dynamically
interact with engine/inference.py.Statistical Metrics: Adds custom
mathematical utility functions, including a precise percentile
calculator ($P_{50}$, $P_{90}$, $P_{99}$) for latency distribution
reporting.Standardized Exports: Lays the groundwork for structured JSON
and CSV output formatting.
Introduces the primary C++ benchmark runner (cpp_benchmark.cpp). It defines the parsing configurations, tracking metrics structures (Stats and BenchRow), and basic time/utility abstractions needed to mirror the Python benchmark suite capabilities.
Added an image to the README for better visualization.
- Define core architecture, compiler hints (`QX_INLINE`, `QX_DEVICE`, etc.). - Implement generic math macros (`CEIL_DIV`, `ROUND_UP`, `NEXT_POW2`). - Add memory alignment utilities targeting 128-byte boundaries. - Implement explicit error-checking macros for CUDA, cuBLAS, and NCCL.
Eamon2009
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May 21, 2026
…45) ## Summary - Project Versioning: Sets the starting project version to 0.1.0. - Code Shortcuts (Macros): Creates clean shorthand terms for CUDA keywords (like wrapping __device__ into QX_DEVICE) to make writing GPU kernels cleaner. - Math & Memory Utilities: Adds fast math helpers for aligning memory, rounding numbers, and calculating power-of-two boundaries quickly. - Memory Optimization: Forces a 128-byte memory alignment to ensure the GPU can read data as fast as possible (coalesced memory access). - Automatic Error Checking: Introduces safety wrappers (CUDA_CHECK, CUBLAS_CHECK, NCCL_CHECK) that instantly watch for crashes or failures in Nvidia's core hardware and math libraries, making debugging much easier.
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Summary
Project Versioning: Sets the starting project version to 0.1.0.
Code Shortcuts (Macros): Creates clean shorthand terms for CUDA keywords (like wrapping device into QX_DEVICE) to make writing GPU kernels cleaner.
Math & Memory Utilities: Adds fast math helpers for aligning memory, rounding numbers, and calculating power-of-two boundaries quickly.
Memory Optimization: Forces a 128-byte memory alignment to ensure the GPU can read data as fast as possible (coalesced memory access).
Automatic Error Checking: Introduces safety wrappers (CUDA_CHECK, CUBLAS_CHECK, NCCL_CHECK) that instantly watch for crashes or failures in Nvidia's core hardware and math libraries, making debugging much easier.