Showing 3 open source projects for "kernel-module-ntfs"

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    DeepGEMM

    DeepGEMM

    Clean and efficient FP8 GEMM kernels with fine-grained scaling

    ...It supports both standard and “grouped” GEMMs, which is useful for architectures like Mixture of Experts (MoE) that require segmented matrix multiplications. One distinguishing aspect is that DeepGEMM compiles its kernels at runtime (via a lightweight Just-In-Time (JIT) module), so users don’t need to precompile CUDA kernels before installation. Despite its lean design, it includes scaling strategies (fine-grained scaling) and optimizations inspired by cutting edge systems (drawing from ideas in CUTLASS, CuTe) but in a more streamlined form.
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  • 2
    FlashMLA

    FlashMLA

    FlashMLA: Efficient Multi-head Latent Attention Kernels

    FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to efficiently manage memory during decoding. ...
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  • 3
    Proximus for Ryzen AI

    Proximus for Ryzen AI

    Runtime extension of Proximus enabling Deployment on AMD Ryzen™ AI

    This project extends the Proximus development environment to support deployment of AI workloads on next-generation AMD Ryzen™ AI processors, such as the Ryzen™ AI 7 PRO 7840U featured in the Lenovo ThinkPad T14s Gen 4 ,one of the first true AI PCs with an onboard Neural Processing Unit (NPU) capable of 16 TOPS (trillion operations per second). Originally designed for use with Windows 11 Pro, this runtime was further enhanced to work under Linux environments, allowing developers and...
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