Tracked topic
…Low-precision training with NeMo Megatron Bridge NeMo Megatron Bridge is an open PyTorch-native library within the NVIDIA NeMo framework. It bi-directionally connects Hugging Face and Megatron Core model checkpoints…
…Newton-Schulz iterations. These measurements were achieved using NVIDIA NeMo Megatron Bridge 26.02 , a PyTorch-native library within the NeMo Framework that provides pretraining, SFT, and LoRA for popular LLM and…
…This open-source library is available on the TensorRT-LLM GitHub repo and includes a modular Python runtime, PyTorch-native model authoring, and a stable production API. Open-Source Frameworks Deploy Nemotron…
…device. Developers can easily integrate high-throughput compression directly into their Python workflows (such as PyTorch or TensorFlow). Measured checkpoint compression ratios We fine-tuned two model architectures (dense transformer and mixture…
…Numba, Triton or PyTorch. Understand the optimization workflows provided by NVIDIA Nsight Compute UI and its ncu command line interface. Use the new scoreboard dependency analysis view and source page improvements like…
…Operability with, for example, SciPy, CuPy, and PyTorch sparse tensors maps common formats like COO, CSR, and DIA to the corresponding DSL of the UST. However, developers can also define their own…
…With DLPack interoperability, tensors from frameworks such as PyTorch, JAX, and CuPy can be converted into cuda::std::mdspan views with cuda::to_device_mdspan for use in C++ kernels, and cuda…
…GMS restore path with pluggable backends (GDS, UCX, etc), currently gated on pending CUDA driver patch TensorRT-LLM support Multi-GPU and multi-node support via quiesce/resume hooks for PyTorch, NCCL…
…A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads 리서치 문서: A Software-defined Tensor Streaming Multiprocessor for Large-scale Machine Learning 비디오: Enabling PyTorch’s Thousand Ops for Software First…
…Cutting transformer layer time by 34% with kernel-level optimizations The NVIDIA and Sarvam AI teams systematically targeted the most expensive kernels identified in the trace, replacing standard PyTorch implementations with fused…