Floating-Point Arithmetic for FPGAs

In this video, we explain how IEEE 754 floating-point numbers work and demonstrate how to convert values in both directions. You will learn how single-precision and double-precision floating-point numbers are divided into sign, exponent, and mantissa fields, and how those fields are used to represent decimal values. We first convert a single-precision floating-point number into decimal by identifying S, E, and M, evaluating the exponent and mantissa, and applying the floating-point formula. We then perform the reverse process by converting a decimal number into its single-precision floating-point representation. The lesson also covers the special IEEE 754 encodings for zero, infinity, NaN, and subnormal numbers. Finally, we demonstrate the provided Python conversion program and floating-point arithmetic IP cores for addition and multiplication. FPGA textbooks: 💻 Digital Editions (Instant Access + Discount): https://truesightlabs333.com/ 📺 Full playlist:    • Advanced FPGA Course: Verilog Based Roboti...   0:00 Intro 0:29 Floating-Point Format 1:15 Floating-Point to Decimal 3:11 Decimal to Floating-Point 4:54 Special Cases 5:35 Floating-Point IP Explained 5:52 Python Demonstration 7:02 Floating-Point IP Demonstration #Verilog #FPGA #DigitalDesign #FloatingPoint #HDL #Electronics #Engineering