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module pairwise_max #(
    parameter int WIDTH = 8,
    parameter int INDEX_WIDTH = 4
)(
    input signed [WIDTH-1:0] a,
    input signed [WIDTH-1:0] b,

    input [INDEX_WIDTH-1:0] index_a,
    input [INDEX_WIDTH-1:0] index_b,

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How to compile GTKWave for Apple Silicon (M1/M2/M3 Macs)

Based on this tutorial for the M1 Mac, find below a step-by-step guide on how to compile GTKWave from scratch for the M3 MacBook (Pro). See my LinkedIn post with the short announcement here.

Note: it is a prerequisite to have HomeBrew installed (find installation instructions at site).

Steps

1. Install required Homebrew packages

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# Makefile for Sudoku Solver

# Compiler
CC = gcc

# Compiler Flags
CFLAGS = -O3 -march=native -flto -funroll-loops -ffast-math -fomit-frame-pointer -finline-functions -fmerge-all-constants -ffunction-sections -fdata-sections -fstack-protector-strong -falign-functions=32

# Target executable
TARGET = sudoku_solver

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from typing import Optional
import os
import subprocess

import torch


def get_gpu_memory_usage():
    """Get GPU memory usage using nvidia-smi."""
    try:

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from typing import Tuple

import torch
import torch.nn as nn


def conv_block(in_channels: int,
               out_channels: int,
               batch_norm: bool):
    return nn.Sequential(

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import torch.nn as nn
import torch

import torch.nn.functional as F

class Net(nn.Module):
    def __init__(self, input_size=16, hidden_size=32, initial_output_size=5):
        super().__init__()

        self.input_size = input_size

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"""Data taken from paper: Computing's Energy Problem (and what we can do about it) - Mark Horowitz

All output energies are in pJ (pico Joule)
"""

import math

E_INT_ADD_PER_BIT = (0.03 / 8 + 0.1 / 32) / 2

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