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Awesome GitHub RepositoriesDisk-Based Offloading Systems

Mechanisms for moving intermediate query results to local storage when memory limits are reached.

Distinct from Disk Caching Systems: Distinct from general disk caching: focuses on offloading intermediate results during large-scale analytical operations.

Explore 3 awesome GitHub repositories matching data & databases · Disk-Based Offloading Systems. Refine with filters or upvote what's useful.

Awesome Disk-Based Offloading Systems GitHub Repositories

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  • prestodb/prestoprestodb 的头像

    prestodb/presto

    16,711在 GitHub 上查看↗

    Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing

    Moves intermediate results to local storage when memory usage exceeds defined limits to allow completion of large-scale operations.

    Javabig-datadatahadoop
    在 GitHub 上查看↗16,711
  • cg123/mergekitcg123 的头像

    cg123/mergekit

    7,158在 GitHub 上查看↗

    Mergekit is a toolkit for combining multiple pretrained large language models into a single model. It functions as an architecture assembler and merging system that transfers capabilities between models using weighted algorithms and layer-wise assembly without requiring additional training. The project provides specialized utilities for extracting low-rank approximations from fine-tuned models to create portable parameter updates. It also includes a framework for converting dense language models into a mixture of experts architecture by constructing gating mechanisms to route inputs to specia

    Implements disk-based sharded loading to enable large-scale model merging on hardware with limited RAM.

    Python
    在 GitHub 上查看↗7,158
  • mseitzer/pytorch-fidmseitzer 的头像

    mseitzer/pytorch-fid

    3,849在 GitHub 上查看↗

    pytorch-fid is a PyTorch-based evaluator and image distribution analysis library used to calculate the Fréchet Inception Distance. It functions as a benchmarking tool that maps image pixels to high-dimensional feature vectors using a pre-trained convolutional neural network to measure the mathematical divergence between real and synthetic datasets. The library quantifies the quality and diversity of generative models by representing image feature sets as mean and covariance matrices. It allows for the extraction of latent representations from specific neural network layers, with configurable

    Persists computed distribution parameters to disk to eliminate redundant neural network passes across multiple evaluations.

    Pythondeep-learningfidfid-score
    在 GitHub 上查看↗3,849
  1. Home
  2. Data & Databases
  3. Disk Caching Systems
  4. Disk-Based Offloading Systems

探索子标签

  • Statistical Parameter CachingPersisting computed distribution parameters to disk to avoid redundant neural network passes. **Distinct from Disk-Based Offloading Systems:** Distinct from Disk-Based Offloading Systems: focuses on caching pre-computed statistical parameters for evaluation, not intermediate query results.
  • Weight ShardingProcesses large model tensors in small chunks from storage to perform merges on hardware with limited system memory. **Distinct from Disk-Based Offloading Systems:** Focuses on sharding large model weights for merging rather than offloading analytical query results