PYTORCH

Explore TorchNeuron, the native PyTorch backend for AWS Trainium that optimizes high-performance deep learning model training and inference. Learn how to integrate it with modern LLM workflows and API aggregators like n1n.ai.

Explore how Zephon integrates with TorchTitan to deliver elastically deterministic data loading for large-scale LLM training, ensuring reproducibility and fault tolerance.

An in-depth technical breakdown of Keras issue #22561, exploring how 15 targeted PRs eliminated graph breaks and reduced Python call overhead to make compiled Keras[torch] 11.6x faster.

A comprehensive developer guide on deploying PyTorch models directly to resource-constrained Arm Cortex-M microcontrollers using ExecuTorch without framework conversion.

An in-depth technical review of how the PyTorch ecosystem transitioned the IBM Spyre accelerator backend from sendnn to torch.compile backend=inductor.

An in-depth analysis of how PyTorch is unifying media processing workflows through TorchCodec, TorchVision, and Torchaudio.

An in-depth technical analysis of PyTorch hardware enablement, exploring how the Accelerator Integration Working Group standardizes PrivateUse1, custom device backends, and torch.compile integrations across heterogenous AI hardware.

A technical deep dive into how Spyre leverages PyTorch's PrivateUse1 architecture to enable high-performance hardware acceleration for deep learning workflows.

An in-depth look at optimizing agentic workloads using NVIDIA Dynamo, focusing on session-aware inference, prefill management, and performance scaling.

A deep dive into the FBTriton kernel design for Table Batched Embedding (TBE) operators, exploring how to scale high-performance recommendation systems.

Discover how integrating Helion—an autotuned high-level kernel DSL—into vLLM's linear backend dramatically boosts LLM inference throughput while maintaining multi-GPU portability.

An in-depth technical analysis of Jagged Flash Attention (JFA) optimized via Tile Language Extensions (TLX) on NVIDIA Blackwell B200 GPUs, paving the way toward FlashAttention-4.