Visible to Intel only — GUID: GUID-CC033F6F-32B3-4E08-852B-AD89678E6431
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
Visible to Intel only — GUID: GUID-CC033F6F-32B3-4E08-852B-AD89678E6431
GPU Flow
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.