Floating Point Library IP Core (FPLIC)

✨ IEEE 754 Compliant

Overview

The Floating Point Library IP Core (FPLIC) from Dillon Engineering provides a comprehensive set of IEEE 754 compliant floating-point arithmetic operations optimized for FPGA implementation. These modules enable high-precision numerical processing in hardware with performance far exceeding software implementations.

Available Operations

➕ Addition/Subtraction

Single and double precision floating point add/subtract with full IEEE 754 compliance including denormalized numbers and exception handling.

✖️ Multiplication

High-performance floating point multiplier with optimized DSP48 block utilization and configurable latency.

➗ Division

Efficient floating point division implementation with configurable precision and throughput trade-offs.

√ Square Root

Hardware square root extraction with iterative or pipelined architecture options.

🔄 Conversion

Fixed-to-float, float-to-fixed, and format conversion operations (single ↔ double precision).

🔍 Comparison

Full suite of comparison operations (equal, less than, greater than) with proper NaN and infinity handling.

Technical Specifications

Parameter Single Precision Double Precision
Format 32-bit IEEE 754 64-bit IEEE 754
Mantissa Bits 23 bits 52 bits
Exponent Bits 8 bits 11 bits
Dynamic Range ~10^±38 ~10^±308
Precision ~7 decimal digits ~15 decimal digits
Add/Sub Latency 6-8 clocks 8-10 clocks
Multiply Latency 4-6 clocks 6-8 clocks
Divide Latency 24-32 clocks 54-64 clocks

Key Features

Performance Characteristics

Throughput

All floating point operations support high-throughput pipelined operation:

Clock Frequency

Achievable clock frequencies on modern Xilinx FPGAs:

Device Family Single Precision Double Precision
Xilinx 7-Series 300-400 MHz 250-350 MHz
UltraScale 400-500 MHz 350-450 MHz
UltraScale+ 450-600 MHz 400-500 MHz

Resource Utilization

Typical FPGA resource usage for single precision operations:

Operation LUTs FFs DSP48 BRAM
Add/Subtract ~500 ~600 0 0
Multiply ~300 ~400 2-3 0
Divide ~2000 ~2500 2-3 0
Square Root ~1800 ~2200 2 0

Applications

Scientific Computing

High-precision numerical applications:

Signal Processing

Advanced DSP algorithms requiring floating-point precision:

Graphics and Visualization

Real-time rendering and processing:

Financial Modeling

High-speed numerical calculations:

Design Considerations

Fixed-Point vs Floating-Point

Use Floating-Point When:

  • Dynamic range requirements are high
  • Precision requirements vary across the computation
  • Algorithm development time is critical
  • Porting from software implementations

Use Fixed-Point When:

  • Resource constraints are tight
  • Maximum performance is required
  • Power consumption is critical
  • Dynamic range is limited and known

Evaluation Package

A free evaluation package is available including:

Supported Simulators

Licensing Options

Flexible licensing to meet your project needs:

Support and Services

Dillon Engineering provides comprehensive support:

Get Started Today

Download the free evaluation package or contact Dillon Engineering for licensing information, technical specifications, or to discuss your floating-point FPGA design requirements.

Email: info@dilloneng.com

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