---
title: "Bitwise Determinism"
description: "1 posts about Bitwise Determinism, summarised, each linking to the original."
---

# Bitwise Determinism
> 1 posts about Bitwise Determinism, summarised, each linking to the original.

## Articles

### [Scale Bitwise-Deterministic Pretraining with NVIDIA Megatron Core](https://yomu.fyi/post/scale-bitwise-deterministic-pretraining-with-nvidia-megatron-core.md)
- Company: [NVIDIA](https://yomu.fyi/company/nvidia-developer-blog.md)
- Author: Ashwath Aithal
- Published: Oct 6, 2026
- Type: Explainer

Bitwise determinism ensures independent and checkpoint-resumed training runs follow the same numerical trajectory, providing four key benefits: replaying failures, preserving checkpoint continuity, detecting unexpected differences, and comparing changes without run-to-run variation. At trillion-parameter scale across thousands of GPUs, nondeterminism complicates failure reproduction and fix validation. NVIDIA Megatron Core targets two guarantees: independent reproducibility and bitwise checkpoint resume. The post describes a validation procedure using full-precision metrics and a progressive tracing workflow that uses torch.hash\_tensor for GPU-resident fingerprints to narrow divergence from end-to-end metrics to the responsible kernel. A Nemotron case study demonstrates that kernel optimizations, such as separating grouped-GEMM writers and applying a fixed reduction order, can reduce the determinism performance overhead to approximately 2% steady-state determinism tax at scale.