1. Introduction to Intel® FPGA Design Flow for AMD* Xilinx* Users
2. Technology Comparison
3. FPGA Tools Comparison
4. AMD* Xilinx* to Intel® FPGA Design Conversion
5. Conclusion
6. AN 307: Intel® FPGA Design Flow for AMD* Xilinx* Users Archives
7. Document Revision History for Intel® FPGA Design Flow for AMD* Xilinx* Users
3.3.1. Project Creation
3.3.2. Design Entry
3.3.3. IP Status
3.3.4. Design Constraints
3.3.5. Synthesis
3.3.6. Design Implementation
3.3.7. Finalize Pinout
3.3.8. Viewing and Editing Design Placement
3.3.9. Static Timing Analysis
3.3.10. Generation of Device Programming Files
3.3.11. Power Analysis
3.3.12. Simulation
3.3.13. Hardware Verification
3.3.14. View Netlist
3.3.15. Design Optimization
3.3.16. Techniques to Improve Productivity
3.3.17. Partial Reconfiguration
3.3.18. Cross-Probing in the Quartus® Prime Pro Edition Software
4.2.1.2.1. Memory Mode
4.2.1.2.2. Clocking Mode
4.2.1.2.3. Write and Read Operation Triggering
4.2.1.2.4. Read-During-Write Operation at the Same Address
4.2.1.2.5. Error Correction Code (ECC)
4.2.1.2.6. Byte Enable
4.2.1.2.7. Address Clock Enable
4.2.1.2.8. Parity Bit Support
4.2.1.2.9. Memory Initialization
4.2.1.2.10. Output Synchronous Set/Reset
3.3.15.4. Fractal Synthesis
Fractal Synthesis optimizations can be used for deep-learning accelerators and other high-throughput, arithmetic-intensive designs that exceed all available DSP resources. For such designs, fractal synthesis optimization can achieve 20-45% area reduction.
Fractal synthesis uses techniques such as multiplier regularization and retiming which are ideal for operations like calculating dot-products, and continuous arithmetic packing to pack adder trees, multipliers into logic blocks optimally sized to fit Intel FPGA LABs.