intel/BigDL

Health v2 · maintenance only

Flags: archived

Adoption not part of the score

2698 stars · 730 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

BigDL is Intel's distributed deep learning library that scales TensorFlow, Keras, and PyTorch workloads on Apache Spark, Flink, and Ray, with sub-libraries for LLM inference, time series (Chronos), recommendations (Friesian), and SGX-secured analytics (PPML). Intel has announced the project will be archived by June 30, 2026, with LLM development moved to IPEX-LLM.

Use cases

• run distributed pytorch training on apache spark
• scale tensorflow keras pipelines from laptop to cluster
• accelerate deep learning on intel cpus and gpus
• time series forecasting with automl on big data
• build recommendation systems at scale
• run big data ai workloads with sgx hardware security
• distributed llm inference on intel hardware

When to choose

• you already run Spark/Flink/Ray clusters and need deep learning integrated into them
• you need SGX/TDX-secured big data AI pipelines (PPML)
• you maintain an existing BigDL-based deployment and can fork it

When to avoid

• starting a new project - Intel is archiving it by 6/30/2026 with no further support
• you only need LLM inference on Intel hardware - use IPEX-LLM instead
• you want actively maintained distributed training - use PyTorch DDP, Ray Train, or Spark-native alternatives

Facets

library · maturity abandoned

deep-learning machine-learning llm-training data-science etl streaming deep-learning machine-learning big-data data-science microservices time-series python jvm cloud apache-spark ray distributed-training tensorflow pytorch keras intel-hardware analytics-zoo recommendation-systems time-series-forecasting sgx-security deprecated gpu docker

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markdown · JSON · MCP: product_card(name="intel/BigDL")