Batch Analytics

New Machine Learning (ML) and Artificial Intelligence (AI) workloads are pushing the limits of scale and processing power of distributed systems and enterprise data centers. There is considerable effort focused on increasing compute density with hardware accelerators such as GPUs, FPGAs, and even custom ASICs.

While hardware accelerators show great promise in terms of processing power and computation throughput, they add a level of development complexity. They also require new associated development and design skills that can considerably lengthen development cycles and time-to-market for new ML and AI projects.

  • Feature Extraction
  • Model Training
  • Model Deployment

There are numerous opportunities for Bigstream Hyperacceleration to speed the time-to-insight for machine learning and AI projects:

Bigstream Benchmark Report

Read the Bigstream Benchmark Report to see specific Apache Spark acceleration results.

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