# Multi Precision This document explains the multi-precision option for bit-width assignment for integers. The multi-precision option enables the frontend to use the smallest bit-width possible for each operation in Fully Homomorphic Encryption (FHE), improving computation efficiency. ## Bit-width and encoding differences Each integer in the circuit has a certain bit-width, which is determined by the input-set. These bit-widths are visible when graphs are printed, for example: ``` %0 = x # EncryptedScalar ∈ [0, 7] %1 = y # EncryptedScalar ∈ [0, 15] %2 = add(%0, %1) # EncryptedScalar ∈ [2, 22] return %2 ^ these are ^^^^^^^ the assigned based on bit-widths these bounds ``` However, adding integers with different bit-widths (for example, 3-bit and 4-bit numbers) directly isn't possible due to differences in encoding, as shown below: ``` D: data N: noise 3-bit number ------------ D2 D1 D0 0 0 0 ... 0 0 0 N N N N 4-bit number ------------ D3 D2 D1 D0 0 0 0 ... 0 0 0 N N N N ``` When you add a 3-bit number and a 4-bit number, the result is a 5-bit number with a different encoding: ``` 5-bit number ------------ D4 D3 D2 D1 D0 0 0 0 ... 0 0 0 N N N N ``` ## Bit-width assignment with graph processing To address these encoding differences, a graph processing step called bit-width assignment is performed. This step updates the graph's bit-widths to ensure compatibility with Fully Homomorphic Encryption (FHE). After this step, the graph might look like this: ``` %0 = x # EncryptedScalar %1 = y # EncryptedScalar %2 = add(%0, %1) # EncryptedScalar return %2 ``` ## Encoding flexibility with Table Lookup Most operations cannot change the encoding, requiring the input and output bit-widths to remain the same. However, the table lookup operation can change the encoding. For example, consider the following graph: ``` %0 = x # EncryptedScalar ∈ [0, 3] %1 = y # EncryptedScalar ∈ [0, 31] %2 = 2 # ClearScalar ∈ [2, 2] %3 = power(%0, %2) # EncryptedScalar ∈ [0, 9] %4 = add(%3, %1) # EncryptedScalar ∈ [1, 39] return %4 ``` This graph represents the computation `(x**2) + y` where `x` is 2-bits and `y` is 5-bits. Without the ability to change encodings, all bit-widths would need to be adjusted to 6-bits. However, since the encoding can change, bit-widths are assigned more efficiently: ``` %0 = x # EncryptedScalar ∈ [0, 3] %1 = y # EncryptedScalar ∈ [0, 31] %2 = 2 # ClearScalar ∈ [2, 2] %3 = power(%0, %2) # EncryptedScalar ∈ [0, 9] %4 = add(%3, %1) # EncryptedScalar ∈ [1, 39] return %4 ``` In this case, `x` remains a 2-bit integer, but the Table Lookup result and `y` are set to 6-bits to allow for the addition. ## Enabling and disabling multi-precision This approach to bit-width assignment is known as multi-precision and is enabled by default. To disable multi-precision and enforce a single precision across the circuit, use the `single_precision=True` configuration option.