1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211
|
#include "Halide.h"
#include "halide_benchmark.h"
#include <algorithm>
#include <cstdio>
using namespace Halide;
using namespace Halide::Tools;
Var x("x"), y("y");
Func bitonic_sort(Func input, int size) {
Func next, prev = input;
Var xo("xo"), xi("xi");
for (int pass_size = 1; pass_size < size; pass_size <<= 1) {
for (int chunk_size = pass_size; chunk_size > 0; chunk_size >>= 1) {
next = Func("bitonic_pass");
Expr chunk_start = (x / (2 * chunk_size)) * (2 * chunk_size);
Expr chunk_end = (x / (2 * chunk_size) + 1) * (2 * chunk_size);
Expr chunk_middle = chunk_start + chunk_size;
Expr chunk_index = x - chunk_start;
if (pass_size == chunk_size && pass_size > 1) {
// Flipped pass
Expr partner = 2 * chunk_middle - x - 1;
// We need a clamp here to help out bounds inference
partner = clamp(partner, chunk_start, chunk_end - 1);
next(x) = select(x < chunk_middle,
min(prev(x), prev(partner)),
max(prev(x), prev(partner)));
} else {
// Regular pass
Expr partner = chunk_start + (chunk_index + chunk_size) % (chunk_size * 2);
next(x) = select(x < chunk_middle,
min(prev(x), prev(partner)),
max(prev(x), prev(partner)));
}
if (pass_size > 1) {
next.split(x, xo, xi, 2 * chunk_size);
}
if (chunk_size > 128) {
next.parallel(xo);
}
next.compute_root();
prev = next;
}
}
return next;
}
// Merge sort contiguous chunks of size s in a 1d func.
Func merge_sort(Func input, int total_size) {
std::vector<Func> stages;
Func result;
const int parallel_work_size = 512;
Func parallel_stage("parallel_stage");
// First gather the input into a 2D array of width four where each row is sorted
{
assert(input.dimensions() == 1);
// Use a small sorting network
Expr a0 = input(4 * y);
Expr a1 = input(4 * y + 1);
Expr a2 = input(4 * y + 2);
Expr a3 = input(4 * y + 3);
Expr b0 = min(a0, a1);
Expr b1 = max(a0, a1);
Expr b2 = min(a2, a3);
Expr b3 = max(a2, a3);
a0 = min(b0, b2);
a1 = max(b0, b2);
a2 = min(b1, b3);
a3 = max(b1, b3);
b0 = a0;
b1 = min(a1, a2);
b2 = max(a1, a2);
b3 = a3;
result(x, y) = select(x == 0, b0,
select(x == 1, b1,
select(x == 2, b2, b3)));
result.compute_at(parallel_stage, y).bound(x, 0, 4).unroll(x);
stages.push_back(result);
}
// Now build up to the total size, merging each pair of rows
for (int chunk_size = 4; chunk_size < total_size; chunk_size *= 2) {
// "result" contains the sorted halves
assert(result.dimensions() == 2);
// Merge pairs of rows from the partial result
Func merge_rows("merge_rows");
RDom r(0, chunk_size * 2);
// The first dimension of merge_rows is within the chunk, and the
// second dimension is the chunk index. Keeps track of two
// pointers we're merging from and an output value.
merge_rows(x, y) = Tuple(0, 0, cast(input.value().type(), 0));
Expr candidate_a = merge_rows(r - 1, y)[0];
Expr candidate_b = merge_rows(r - 1, y)[1];
Expr valid_a = candidate_a < chunk_size;
Expr valid_b = candidate_b < chunk_size;
Expr value_a = result(clamp(candidate_a, 0, chunk_size - 1), 2 * y);
Expr value_b = result(clamp(candidate_b, 0, chunk_size - 1), 2 * y + 1);
merge_rows(r, y) = select(valid_a && ((value_a < value_b) || !valid_b),
Tuple(candidate_a + 1, candidate_b, value_a),
Tuple(candidate_a, candidate_b + 1, value_b));
if (chunk_size <= parallel_work_size) {
merge_rows.compute_at(parallel_stage, y);
} else {
merge_rows.compute_root();
}
if (chunk_size == parallel_work_size) {
parallel_stage(x, y) = merge_rows(x, y)[2];
parallel_stage.compute_root().parallel(y);
result = parallel_stage;
} else {
result = lambda(x, y, merge_rows(x, y)[2]);
}
}
// Convert back to 1D
return lambda(x, result(x, 0));
}
int main(int argc, char **argv) {
Target target = get_jit_target_from_environment();
if (target.arch == Target::WebAssembly) {
printf("[SKIP] Performance tests are meaningless and/or misleading under WebAssembly interpreter.\n");
return 0;
}
const int N = 1 << 10;
Buffer<int> data(N);
for (int i = 0; i < N; i++) {
data(i) = rand() & 0xfffff;
}
Func input = lambda(x, data(x));
printf("Bitonic sort...\n");
Func f = bitonic_sort(input, N);
f.bound(x, 0, N);
f.compile_jit();
printf("Running...\n");
Buffer<int> bitonic_sorted(N);
f.realize(bitonic_sorted);
double t_bitonic = benchmark([&]() {
f.realize(bitonic_sorted);
});
printf("Merge sort...\n");
f = merge_sort(input, N);
f.bound(x, 0, N);
f.compile_jit();
printf("Running...\n");
Buffer<int> merge_sorted(N);
f.realize(merge_sorted);
double t_merge = benchmark([&]() {
f.realize(merge_sorted);
});
Buffer<int> correct(N);
for (int i = 0; i < N; i++) {
correct(i) = data(i);
}
printf("std::sort...\n");
double t_std = benchmark([&]() {
std::sort(&correct(0), &correct(N));
});
printf("Times:\n"
"bitonic sort: %fms \n"
"merge sort: %fms \n"
"std::sort %fms\n",
t_bitonic * 1e3, t_merge * 1e3, t_std * 1e3);
if (N <= 100) {
for (int i = 0; i < N; i++) {
printf("%8d %8d %8d\n",
correct(i), bitonic_sorted(i), merge_sorted(i));
}
}
for (int i = 0; i < N; i++) {
if (bitonic_sorted(i) != correct(i)) {
printf("bitonic sort failed: %d -> %d instead of %d\n", i, bitonic_sorted(i), correct(i));
return 1;
}
if (merge_sorted(i) != correct(i)) {
printf("merge sort failed: %d -> %d instead of %d\n", i, merge_sorted(i), correct(i));
return 1;
}
}
printf("Success!\n");
return 0;
}
|