SYCLDB – cross-architecture acceleration of data analytics with SYCL (EMEA)
The growing popularity of AI and analytics in virtually all domains has increased the amount of data gathered. Workflows have become increasingly heterogeneous. While CPUs are only sometimes efficient enough for the demands of modern AI and analytics workloads, GPUs, which offer greater parallelism, have remained mainly closed-source. In response, two open standards have gained popularity: RISC-V, an open instruction set architecture, and SYCL, a cross-platform programming model.
Our work combines these two open standards by developing SYCLDB, a SYCL-based library of key relational operations designed to run seamlessly across platforms. Leveraging the oneAPI Construction Kit (OCK), SYCLDB supports RISC-V and accelerators while efficiently utilizing vectorization and multithreading on x64 CPUs and exploiting SIMT parallelism on NVIDIA GPUs. This flexibility does not degrade GPU performance, as SYCLDB achieves results comparable to its CUDA counterpart.
