Showing 3 open source projects for "workload"

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  • 1
    mistral.rs

    mistral.rs

    Fast, flexible LLM inference

    ...The project includes hardware-aware tooling that can benchmark a system and choose sensible quantization and device-mapping strategies, helping users get strong performance without manual tuning. It also supports serving multiple models from the same server process, enabling routing or quick switching between models depending on workload needs. For user-facing testing, mistral.rs can provide a built-in web UI, and it also offers a dedicated lightweight web chat interface that supports richer interaction patterns.
    Downloads: 2 This Week
    Last Update:
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  • 2
    Sail

    Sail

    A drop-in Apache Spark replacement written in Rust

    ...The framework is designed to operate across a variety of environments, including local machines, Kubernetes clusters, and cloud deployments, allowing flexible scaling based on workload requirements. It also emphasizes cost efficiency, with benchmarks showing significant performance improvements and reduced infrastructure usage compared to traditional systems.
    Downloads: 0 This Week
    Last Update:
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  • 3
    uzu

    uzu

    A high-performance inference engine for AI models

    ...The engine implements a hybrid architecture in which model layers can be executed either as custom GPU kernels or through Apple’s MPSGraph API, allowing it to balance performance and compatibility depending on the workload. By utilizing Apple’s unified memory architecture, uzu reduces memory copying overhead and improves inference throughput for local AI workloads. The system includes a simple high-level API that enables developers to run models, create inference sessions, and generate outputs with minimal configuration.
    Downloads: 0 This Week
    Last Update:
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