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https://github.com/ggerganov/llama.cpp.git
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1bfc153e2f
* A faster version for Q4_1 x Q8_0 dot products The idea nehind being that Q8_0 quantized values get used many times in the matrix multiplications where they are involved. In the current implementations, when we are evaluating the dot products, we need to compute the sum of the quants in the Q8_0 vector, so the same operation is repeated many times. Here we pre-compute the sum during Q8_0 quantization, store it in the now modified block_q8_0 struct, and then reuse this result in the subsequent dot products. In a synthetic benchmark (just compute a bunch of dot products), this change speeds up the Q4_1 * Q8_0 dot product by 80%, making the performance identical to Q4_0 * Q8_0. In practical application, I see a ~15% gain in speed for token prediction on M2, and ~5% gain on Ryzen 7950X. The speed gain in the prompt evaluation is much bigger (around 50%). I have only done the change for the scalar version, ARM_NEON, and AVX2, so we still need an AVX implementation. * Cleaning up --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
173 lines
5.2 KiB
C++
173 lines
5.2 KiB
C++
#include <cstdio>
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#include <type_traits>
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#include <vector>
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#include <random>
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#include <chrono>
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#include <cstdlib>
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#include <cmath>
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#include <cassert>
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#include <cstring>
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#include <array>
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#include <type_traits>
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#include <ggml.h>
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constexpr int kVecSize = 1 << 16;
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// Copy-pasted from ggml.c
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#define QK4_0 32
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typedef struct {
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float d; // delta
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uint8_t qs[QK4_0 / 2]; // nibbles / quants
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} block_q4_0;
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static_assert(sizeof(block_q4_0) == sizeof(float) + QK4_0 / 2, "wrong q4_0 block size/padding");
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#define QK4_1 32
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typedef struct {
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float d; // delta
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float m; // min
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uint8_t qs[QK4_1 / 2]; // nibbles / quants
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} block_q4_1;
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static_assert(sizeof(block_q4_1) == sizeof(float) * 2 + QK4_1 / 2, "wrong q4_1 block size/padding");
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// Copy-pasted from ggml.c
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#define QK8_0 32
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typedef struct {
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float d; // delta
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float s; // d * sum(qs[i])
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int8_t qs[QK8_0]; // quants
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} block_q8_0;
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static_assert(sizeof(block_q8_0) == 2*sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
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static_assert(QK4_1 == QK8_0, "QK4_1 and QK8_0 must be the same");
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static_assert(QK4_0 == QK8_0, "QK4_0 and QK8_0 must be the same");
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template <typename T>
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void fillQ4blocks(std::vector<T>& blocks, std::mt19937& rndm) {
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for (auto& b : blocks) {
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b.d = 1;
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for (int i=0; i<QK4_1/2; ++i) {
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uint8_t v1 = rndm() >> 28;
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uint8_t v2 = rndm() >> 28;
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b.qs[i] = v1 | (v2 << 4);
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}
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}
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}
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void fillQ80blocks(std::vector<block_q8_0>& blocks, std::mt19937& rndm) {
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for (auto& b : blocks) {
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b.d = 1;
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int sum = 0;
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for (int i=0; i<QK8_0; ++i) {
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b.qs[i] = (rndm() >> 24) - 128;
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sum += b.qs[i];
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}
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b.s = b.d * sum;
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}
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}
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float simpleDot(const block_q4_0& x, const block_q8_0& y) {
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int s1 = 0; //, s2 = 0;
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for (int i=0; i<QK4_1/2; i+=2) {
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int v1 = x.qs[i+0] & 0xf;
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int v2 = x.qs[i+0] >> 4;
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int v3 = x.qs[i+1] & 0xf;
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int v4 = x.qs[i+1] >> 4;
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int j = 2*i;
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s1 += v1*y.qs[j] + v2*y.qs[j+1] + v3*y.qs[j+2] + v4*y.qs[j+3];
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//s2 += y.qs[j] + y.qs[j+1] + y.qs[j+2] + y.qs[j+3];
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}
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return y.d * x.d * s1 - 8 * x.d * y.s;
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//return y.d * x.d * (s1 - 8 * s2);
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}
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float simpleDot(const block_q4_1& x, const block_q8_0& y) {
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int s1 = 0; //, s2 = 0;
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for (int i=0; i<QK4_1/2; i+=2) {
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int v1 = x.qs[i+0] & 0xf;
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int v2 = x.qs[i+0] >> 4;
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int v3 = x.qs[i+1] & 0xf;
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int v4 = x.qs[i+1] >> 4;
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int j = 2*i;
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s1 += v1*y.qs[j] + v2*y.qs[j+1] + v3*y.qs[j+2] + v4*y.qs[j+3];
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//s2 += y.qs[j] + y.qs[j+1] + y.qs[j+2] + y.qs[j+3];
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}
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return y.d * x.d * s1 + y.s * x.m;
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//return y.d * (x.d * s1 + x.m * s2);
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}
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struct Stat {
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double sum = 0, sumt = 0, sumt2 = 0, maxt = 0;
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int nloop = 0;
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void addResult(double s, double t) {
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sum += s;
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sumt += t; sumt2 += t*t; maxt = std::max(maxt, t);
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++nloop;
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}
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void reportResult(const char* title) const {
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if (nloop < 1) {
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printf("%s(%s): no result\n",__func__,title);
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return;
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}
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printf("============ %s\n",title);
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printf("<dot> = %g\n",sum/nloop);
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auto t = sumt/nloop, dt = sumt2/nloop - t*t;
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if (dt > 0) dt = sqrt(dt);
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printf("<time> = %g +/- %g us. Max. time = %g us.\n",t,dt,maxt);
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}
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};
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int main(int argc, char** argv) {
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int nloop = argc > 1 ? atoi(argv[1]) : 10;
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int type = argc > 2 ? atoi(argv[2]) : 1;
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std::mt19937 rndm(1234);
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std::vector<block_q4_1> x41;
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std::vector<block_q4_0> x40;
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std::vector<block_q8_0> y(kVecSize);
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if (type == 0) x40.resize(kVecSize);
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else {
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x41.resize(kVecSize);
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for (auto& b : x41) b.m = 1;
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}
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auto ggml_type = type == 0 ? GGML_TYPE_Q4_0 : GGML_TYPE_Q4_1;
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auto funcs = ggml_internal_get_quantize_fn(ggml_type);
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Stat simple, ggml;
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for (int iloop=0; iloop<nloop; ++iloop) {
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if (type == 0) fillQ4blocks(x40, rndm);
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else fillQ4blocks(x41, rndm);
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fillQ80blocks(y, rndm);
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auto t1 = std::chrono::high_resolution_clock::now();
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double s = 0;
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if (type == 0) for (int i=0; i<kVecSize; ++i) s += simpleDot(x40[i], y[i]);
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else for (int i=0; i<kVecSize; ++i) s += simpleDot(x41[i], y[i]);
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auto t2 = std::chrono::high_resolution_clock::now();
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auto t = 1e-3*std::chrono::duration_cast<std::chrono::nanoseconds>(t2-t1).count();
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if (iloop > 3) simple.addResult(s, t);
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t1 = std::chrono::high_resolution_clock::now();
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float fs;
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if (type == 0) funcs.vec_dot_q(kVecSize * QK4_1, &fs, x40.data(), y.data());
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else funcs.vec_dot_q(kVecSize * QK4_1, &fs, x41.data(), y.data());
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t2 = std::chrono::high_resolution_clock::now();
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t = 1e-3*std::chrono::duration_cast<std::chrono::nanoseconds>(t2-t1).count();
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if (iloop > 3) ggml.addResult(fs, t);
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}
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// Report the time (and the average of the dot products so the compiler does not come up with the idea
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// of optimizing away the function calls after figuring that the result is not used).
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simple.reportResult("Simple");
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ggml.reportResult("ggml");
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return 0;
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}
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