Intel FPGAs speed up databases with oneAPI and SIMD orders
FPGAs are known for high-performance computing via customizing circuits for algorithms. Their tailored and optimized hardware accelerates difficult computations
SIMD parallel processing applies a single instruction to numerous data objects. Special hardware extensions can execute the same instruction on several data objects simultaneously
Specialized implementations limit portability between platforms, hence SIMD abstraction libraries provide a common SIMD interface and abstract SIMD functions
Traditional FPGAs required a strong understanding of digital design concepts and specific languages like VHDL or Verilog
The scalar code specifies loading registers, and the pragma unroll attribute tells the DPC++ Compiler to implement all pathways in parallel in the generic element-wise addition
First, they gradually increased the SIMD instance register width to see how it affected maximum acceleration bandwidth
The second scenario, a filter-count kernel with a data dependency in the last stage of the adder tree, demonstrated similar behavior but saturates earlier at the PCIe link width