klotz: gpu*

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  1. CUDA Tile is a new Python package that simplifies GPU programming by automatically tiling loops, handling data transfer, and optimizing memory access. It allows developers to write concise and readable code that leverages the full power of NVIDIA GPUs without needing to manually manage the complexities of parallel programming.
  2. A user shares their optimal settings for running the gpt-oss-120b model on a system with dual RTX 3090 GPUs and 128GB of RAM, aiming for a balance between performance and quality.
  3. A new patch enables Nvidia GPU support on Raspberry Pi 5 and Rockchip devices, allowing for GPU-accelerated compute tasks. The article details the setup process, performance testing with llama.cpp, and current limitations with display output.
  4. This post explores a new idea for parallelizing a simplified parsing task using a "stack monoid" and scan operations, potentially enabling efficient GPU implementation of parsing algorithms.
  5. M5 delivers over 4x the peak GPU compute performance for AI compared to M4, featuring a next-generation GPU with a Neural Accelerator in each core, a more powerful CPU, a faster Neural Engine, and higher unified memory bandwidth.
  6. This article details the integration of Docker Model Runner with the NVIDIA DGX Spark, enabling faster and simpler local AI model development. It covers setup, usage, and benefits like data privacy, offline availability, and ease of customization.
  7. Nvidia's DGX Spark is a relatively affordable AI workstation that prioritizes capacity over raw speed, enabling it to run models that consumer GPUs cannot. It features 128GB of memory and is based on the Blackwell architecture.
  8. Nvidia introduces the Rubin CPX GPU, designed to accelerate AI inference by decoupling the context and generation phases. It utilizes GDDR7 memory for lower cost and power consumption, aiming to redefine AI infrastructure.
  9. The fast, feature-rich, GPU based terminal emulator. It's capable, scriptable, composable, cross-platform, and innovative.
  10. Nvidia has expanded its Jetson lineup with the Jetson AGX Thor Developer Kit, a compact platform that carries the new Jetson T5000 system-on-module. Marketed as a developer system, the dimensions and form factor place it firmly in the realm of a mini PC, although its design and purpose align more with edge AI deployment than home computing.
    2025-08-31 Tags: , , , , , , , by klotz

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