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GPUHammer demonstrates that Rowhammer bit flips are practical on GPU memories, specifically on GDDR6 in NVIDIA A6000 GPUs. By exploiting these vulnerabilities, attackers can significantly degrade the accuracy of machine learning models, highlighting a critical security concern for shared GPU environments.

Kompute is a flexible GPU computing framework supported by the Linux Foundation, offering a Python module and C++ SDK for high-performance asynchronous and parallel processing. It enables easy integration with existing Vulkan applications and includes a robust codebase with extensive testing, making it suitable for machine learning, mobile development, and game development. The platform also supports community engagement through Discord and various educational resources like Colab Notebooks and conference talks.

Researchers have successfully demonstrated a Rowhammer attack against the GDDR6 memory of an NVIDIA A6000 GPU, revealing that a single bit flip could drastically reduce the accuracy of deep neural network models from 80% to 0.1%. Nvidia has acknowledged the findings and suggested enabling error-correcting code (ECC) as a mitigation strategy, although it may impact performance and memory capacity. The researchers have also created a dedicated website for their proof-of-concept code and shared their detailed findings in a published paper.

RAPIDS version 25.06 introduces significant enhancements, including a Polars GPU streaming engine for large dataset processing, a unified API for graph neural networks that streamlines multi-GPU workflows, and zero-code changes for support vector machines, improving performance in existing scikit-learn frameworks. The release also features updates to memory management and compatibility with the latest Python and NVIDIA CUDA versions.