1. Understanding SIMD Architecture for FPGA
SIMD (Single Instruction, Multiple Data) is a parallel processing technique where a single instruction operates on multiple data points simultaneously. For FPGA implementation, we'll focus on:
Image Not Showing
Possible Reasons
- The image was uploaded to a note which you don't have access to
- The note which the image was originally uploaded to has been deleted
Learn More →
- Data Parallelism: Same operation applied to multiple data elements
- Vector Processing: Fixed-width operations on packed data
- Scalability: Configurable number of processing elements (PEs)
2. Core Components of an FPGA SIMD Processor
Processing Element (PE) Design
Vector Register File
- Implement using Block RAM (BRAM)
- Typically 4-16 vector registers
- Each register holds multiple data elements (e.g., 8x32-bit values)
Instruction Set Design
Image Not Showing
Possible Reasons
- The image was uploaded to a note which you don't have access to
- The note which the image was originally uploaded to has been deleted
Learn More →
3. Memory Subsystem
Data Memory Organization
- Interleaved memory banks for parallel access
- Use FPGA BRAM resources (e.g., Xilinx's RAMB36E1)
- Example 4-bank memory architecture:
Memory Controller
4. Interconnection Network
Common Topologies:
- 1D Mesh: Simple linear connection
- Crossbar: Fully connected (resource intensive)
- Tree: Reduced connectivity (good for reductions)
Example Crossbar Implementation:
5. Control Unit Design
VLIW (Very Long Instruction Word) Approach
- Pack multiple operations into wide instructions
- Typical instruction format:
[Opcode PE0][Opcode PE1]...[Opcode PE7][Operand Addr][Dest Addr]
Finite State Machine Example
6. Implementation Considerations
FPGA Resource Utilization
- LUTs: For PE logic and control
- DSP Slices: For arithmetic operations
- Block RAM: For vector registers and memory
- Registers: For pipelining and state storage
Optimization Techniques
- Pipelining: Add pipeline registers between stages
- Time-multiplexing: Share resources when possible
- Data Alignment: Ensure proper memory alignment
- Custom Instructions: Add domain-specific operations
7. Complete SIMD Core Integration
Top-Level Module
8. Verification and Testing
Testbench Structure
9. Advanced Enhancements
Optional Features to Add:
- Predication: Conditional execution
- Masking: Selective element processing
- Reduction Operations: Sum across vector
- Scatter/Gather: Irregular memory access
- Floating-Point Support: Using FPGA DSPs
10. Target FPGA Considerations
For Xilinx Spartan-6 (XC6SLX9):
- 16 DSP48A1 slices available
- 576kb block RAM
- Implement 4-8 PEs efficiently
For Intel Cyclone 10LP:
- Use M9K memory blocks
- DSP blocks for arithmetic
- Optimize for lower power
This implementation provides a flexible SIMD architecture that can be scaled based on your target FPGA's resources and your application requirements. The modular design allows for easy customization of the number of processing elements, data width, and supported operations.