ARM内联汇编代码，错误为“ asm中不可能约束”

Question

I am trying to optimize the following code complex.cpp:

typedef struct {
    float re;
    float im;
} dcmplx;

dcmplx ComplexConv(int len, dcmplx *hat, dcmplx *buf)
{
    int    i;
    dcmplx    z, xout;

    xout.re = xout.im = 0.0;
    asm volatile (
    "movs r3, #0\n\t"
    ".loop:\n\t"
    "vldr s11, [%[hat], #4]\n\t"
    "vldr s13, [%[hat]]\n\t"
    "vneg.f32 s11, s11\n\t"
    "vldr s15, [%[buf], #4]\n\t"
    "vldr s12, [%[buf]]\n\t"
    "vmul.f32 s14, s15, s13\n\t"
    "vmul.f32 s15, s11, s15\n\t"
    "adds %[hat], #8\n\t"
    "vmla.f32 s14, s11, s12\n\t"
    "vnmls.f32 s15, s12, s13\n\t"
    "adds %[buf], #8\n\t"
    "vadd.f32 s1, s1, s14\n\t"
    "vadd.f32 s0, s0, s15\n\t"
    "adds r3, r3, #1\n\t"
    "cmp r3, r0\n\t"
    "bne .loop\n\t"
    : "=r"(xout)
    : [hat]"r"(hat),[buf]"r"(buf) 
    : "s0","cc"
    );
    return xout;
}

When it is compiled with "arm-linux-gnueabihf-g++ -c complex.cpp -o complex.o -mfpu=neon", I got the following error: impossible constraint in 'asm'.

When I comment out "=r"(xout), the compile doesn't complain, but how can I get result of register 's0' into xout?

Besides, how it works if r0 contains return value but the return type is a complicate structure, since r0 is only a 32-bit? register.

The original c code I post here:

dcmplx ComplexConv(int len, dcmplx *hat, dcmplx *buf)
{
    int    i;
    dcmplx    z, xout;
    xout.re = xout.im = 0.0;
    for(int i = 0; i < len; i++) {
        z = BI_dcmul(BI_dconjg(hat[i]),buf[i]);
        xout = BI_dcadd(xout,z);
    }
    return xout;
}
dcmplx BI_dcmul(dcmplx x, dcmplx y)
{
    dcmplx    z;
    z.re = x.re * y.re - x.im * y.im;
    z.im = x.im * y.re + x.re * y.im;
    return z;
}
dcmplx BI_dconjg(dcmplx x)
{
    dcmplx    y;
    y.re = x.re;
    y.im = -x.im;
    return y;
}
dcmplx BI_dcadd(dcmplx x, dcmplx y)
{
    dcmplx    z;
    z.re = x.re + y.re;
    z.im = x.im + y.im;
    return z;
}

Answer 1

Your inline assembly code makes a number of mistakes:

• It tries to use a 64-bit structure as an operand with a 32-bit output register ( "=r" ) constraint. This is what gives you the error.
• It doesn't use that output operand anywhere
• It doesn't tell the compiler where the output actually is (S0/S1)
• It doesn't tell the compiler that len is supposed to be an input
• It clobbers a number of registers, R3, S11, S12, S13, S14, S14, without telling the compiler.
• It uses a label .loop that unnecessarily prevents the compiler from inlining your code in multiple places.
• It doesn't actually appear to be the equivalent of the C++ code you've shown, calculating something else instead.

I'm not going to bother to explain how you can fix all these mistakes, because you shouldn't be using inline assembly . You can write your code in C++ and let the compiler do the vectorization.

For example compiling following code, equivalent to your example C++ code, with GCC 4.9 and the -O3 -funsafe-math-optimizations options:

dcmplx ComplexConv(int len, dcmplx *hat, dcmplx *buf)
{
    int    i;
    dcmplx xout;
    xout.re = xout.im = 0.0;
    for (i = 0; i < len; i++) {
        xout.re += hat[i].re * buf[i].re + hat[i].im * buf[i].im;
        xout.im += hat[i].re * buf[i].im - hat[i].im * buf[i].re;
    }
    return xout;
}

generates the following assembly as its inner loop:

.L97:
    add lr, lr, #1
    cmp ip, lr
    vld2.32 {d20-d23}, [r5]!
    vld2.32 {d24-d27}, [r4]!
    vmul.f32    q15, q12, q10
    vmul.f32    q14, q13, q10
    vmla.f32    q15, q13, q11
    vmls.f32    q14, q12, q11
    vadd.f32    q9, q9, q15
    vadd.f32    q8, q8, q14
    bhi .L97

Based on your inline assembly code, it's likely that the compiler generated better than what you would've come up with if you tried to vectorize it yourself.

The -funsafe-math-optimizations is necessary because the NEON instructions aren't fully IEEE 754 conformant. As the GCC documentation states:

If the selected floating-point hardware includes the NEON extension (eg -mfpu='neon' ), note that floating-point operations are not generated by GCC's auto-vectorization pass unless -funsafe-math-optimizations is also specified. This is because NEON hardware does not fully implement the IEEE 754 standard for floating-point arithmetic (in particular denormal values are treated as zero), so the use of NEON instructions may lead to a loss of precision.

I should also note that the compiler generates almost as good as code above if you don't roll your own complex type, like in the following example:

#include <complex>
typedef std::complex<float> complex;
complex ComplexConv_std(int len, complex *hat, complex *buf)
{
    int    i;
    complex xout(0.0f, 0.0f); 
    for (i = 0; i < len; i++) {
        xout += std::conj(hat[i]) * buf[i];
    }
    return xout;
}

One advantage to using your own type however, is that you can improve the code compiler generates making one small change to how you declare struct dcmplx :

typedef struct {
    float re;
    float im;
} __attribute__((aligned(8)) dcmplx;

By saying it needs to be 8-byte (64-bit) aligned, this allows the compiler to skip the check to see if it is suitably aligned and then fall back on the slower scalar implementation instead.

Now, hypothetically, lets say you were unsatisfied with how GCC vectorized your code and thought you could do better. Would this justify using inline assembly? No, the next thing to try are the ARM NEON intrinsics . Using intrinics is just like normal C++ programming, you don't have worry about a bunch of special rules you need to follow. For example here's how I converted the vectorized assembly above into this untested code that uses intrinsics:

#include <assert.h>
#include <arm_neon.h>
dcmplx ComplexConv(int len, dcmplx *hat, dcmplx *buf)
{
    int    i;
    dcmplx xout;

    /* everything needs to be suitably aligned */
    assert(len % 4 == 0);
    assert(((unsigned) hat % 8) == 0);
    assert(((unsigned) buf % 8) == 0);

    float32x4_t re, im;
    for (i = 0; i < len; i += 4) {
        float32x4x2_t h = vld2q_f32(&hat[i].re);
        float32x4x2_t b = vld2q_f32(&buf[i].re);
        re = vaddq_f32(re, vmlaq_f32(vmulq_f32(h.val[0], b.val[0]),
                                     b.val[1], h.val[1]));
        im = vaddq_f32(im, vmlsq_f32(vmulq_f32(h.val[1], b.val[1]),
                                     b.val[0], h.val[0]));
    }
    float32x2_t re_tmp = vadd_f32(vget_low_f32(re), vget_high_f32(re));
    float32x2_t im_tmp = vadd_f32(vget_low_f32(im), vget_high_f32(im));
    xout.re = vget_lane_f32(vpadd_f32(re_tmp, re_tmp), 0);
    xout.im = vget_lane_f32(vpadd_f32(im_tmp, im_tmp), 0);
    return xout;
}

Finally if this wasn't good enough and you needed to tweak out every bit of performance you could then it's still not a good idea to use inline assembly. Instead your last resort should be to use regular assembly instead. Since your rewriting most of the function in assembly, you might as well write it completely in assembly. That means you don't have worry about telling the compiler about everything you're doing in the inline assembly. You only need to conform to the ARM ABI, which can be tricky enough, but is a lot easier than getting everything correct with inline assembly.