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Why is FPGA Compilation Different? Types of SYCL* FPGA Compilation FPGA Compilation Flags Emulate and Debug Your Design Evaluate Your Kernel Through Simulation Device Selectors for FPGA FPGA IP Authoring Flow Fast Recompile for FPGA Generate Multiple FPGA Images (Linux only) FPGA BSPs and Boards Targeting Multiple Homogeneous FPGA Devices Targeting Multiple Platforms FPGA-CPU Interaction FPGA Performance Optimization Use of RTL Libraries for FPGA Use SYCL Shared Library With Third-Party Applications FPGA Workflows in IDEs
Intel oneAPI DPC++ Library (oneDPL) Intel oneAPI Math Kernel Library (oneMKL) Intel oneAPI Threading Building Blocks (oneTBB) Intel oneAPI Data Analytics Library (oneDAL) Intel oneAPI Collective Communications Library (oneCCL) Intel oneAPI Deep Neural Network Library (oneDNN) Intel oneAPI Video Processing Library (oneVPL) Other Libraries
GPUs are special-purpose compute devices that can be used to offload a compute intensive portion of your application. GPUs usually consists of many smaller cores and are therefore known for massive throughput. There are some tasks better suited to a CPU and others that may be better suited to a GPU.
TIP:Unsure whether your workload fits best on CPU, GPU, or FPGA? Compare the benefits of CPUs, GPUs, and FPGAs for different oneAPI compute workloads.
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