Udp

Big data analytic applications give rise to large-scale extract-transform-load (ETL) as a fundamental step to transform new data into a native representation. ETL workloads pose significant performance challenges on conventional architectures, so we propose the design of the unstructured data processor (UDP), a software programmable accelerator that includes multi-way dispatch, variable-size symbol support, Flexible-source dispatch (stream buffer and scalar registers), and memory addressing to accelerate ETL kernels both for current and novel future encoding and compression. Specifically, UDP excels at branch-intensive and symbol and pattern-oriented workloads, and can offload them from CPUs.