riscvsoftware.md

Step 1: Setting Up Ubuntu within VMBox

1. Install Ubuntu on VMBox.
2. Launch Ubuntu's terminal.

Step 2: Install Leafpad

$ sudo apt install leafpad

Navigate to the home directory:

$ cd

$ leafpad filename.c &

Step 3: Compile and Run the C Code

Compile the C code:

$ gcc filename.c

Run the compiled program:

$ ./a.out

Step 4: Compile C Code with RISC-V Compiler

Compile the C code using the RISC-V compiler:

$ riscv64-unknown-elf-gcc -O1 -mabi=lp64 -march=rv64i -o filename.o filename.c

List the compiled object file:

$ ls -ltr filename.o

Step 5: Display Assembly Code

Display the optimized assembly code for the main function:

$ riscv64-unknown-elf-objdump -d filename.o | less

Binary Neural Network in C

int main(int argc, char* argv[])
{
    srand(0); // Use a fixed random seed for debugging.

    // Initialize layers.
    Layer* linput = Layer_create(NULL, 2);
    Layer* lhidden = Layer_create(linput, 3);
    Layer* loutput = Layer_create(lhidden, 1);
    Layer_dump(linput, stderr);
    Layer_dump(lhidden, stderr);
    Layer_dump(loutput, stderr);

    // Run the network.
    double rate = 1.0;
    int nepochs = 10000;
    for (int i = 0; i < nepochs; i++) {
        double x[2];
        double y[1];
        double t[1];
        x[0] = rnd();
        x[1] = rnd();
        t[0] = f(x[0], x[1]);
        Layer_setInputs(linput, x);
        Layer_getOutputs(loutput, y);
        Layer_learnOutputs(loutput, t);
        double etotal = Layer_getErrorTotal(loutput);
        fprintf(stderr, "i=%d, x=[%.4f, %.4f], y=[%.4f], t=[%.4f], etotal=%.4f\n",
                i, x[0], x[1], y[0], t[0], etotal);
        Layer_update(loutput, rate);
    }

    // Dump the finished network.
    Layer_dump(linput, stdout);
    Layer_dump(lhidden, stdout);
    Layer_dump(loutput, stdout);

    // Free the memory.
    Layer_destroy(linput);
    Layer_destroy(lhidden);
    Layer_destroy(loutput);
    return 0;
}