Relational query processing on OpenCL-based FPGAs

Abstract

The release of OpenCL support for FPGAs represents a significant improvement in extending database applications to the reconfigurable domain. Taking advantage of the programmability offered by the OpenCL HLS tool, an OpenCL database can be easily ported and re-designed for FPGAs. A single SQL query in these database systems usually consists of multiple operators, and each one of these operators in turn consists of multiple OpenCL kernels. Due to the specific properties of FPGAs, each OpenCL kernel can have different FPGA-specific optimization combinations, in terms of CU (compute unit) and SIMD (kernel vectorization), which are critical to the overall performance of query processing. Due to the resource limitation of an FPGA image, our query plan also considers the possibility of using multiple FPGA images. In this paper, we propose an FPGA-specific cost model to determine the optimal query plan in less than one minute. In particular, the FPGA synthesis time is significantly reduced by avoiding the need to evaluate all the feasible query plans on real FPGAs. Our cost model has two components: unit cost and optimal query plan generation. The first component generates multiple (unit cost, resource utilization) pairs for each kernel. The second component employs a dynamic programming approach to generate the optimal query plan which considers the possibility of using multiple FPGA images. The experiments show that 1) our cost model can accurately predict the performance of each feasible query plan for the input query, and can guide the optimal query plan generation, 2) our optimized query plan achieves a performance speedup 1.5×–4× over the state-of-the-art query processing on OpenCL-based FPGAs.