Bigstream makes Big Data, ML and AI workloads faster through a technique called Hyper-acceleration. Bigstream developed Hyper-acceleration to deliver orders of magnitude performance gains for Apache Spark using hardware and software accelerators. Hyper-acceleration of big data and ML workloads is achieved using advanced compiler technology and transparent support for FPGAs. Unlike other approaches, Bigstream requires no application code changes or special APIs. Hyper-acceleration is a technology that enables big data and machine learning applications to automatically utilize the power of unconventional hardware (e.g. GPUs, FPGAs) as well as software optimizations with many-core CPUs. The Bigstream Hyper-acceleration Layer (HaL) functions as a runtime system that sits between a software platform (such as Apache Spark, or TensorFlow) and the underlying hardware to slice and distribute the computation between traditional CPU cores and different accelerator resources.
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