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https://github.com/ClickHouse/ClickHouse.git
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rand isn't avx2-vectorizable, I give it up
This commit is contained in:
Dmitrii Kovalkov
parent
e603158571
commit
feaed1e020
@ -1,5 +1,6 @@
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#include <Functions/FunctionFactory.h>
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#include <Functions/FunctionsRandom.h>
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#include <Functions/VectorExtension.h>
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#include <Common/HashTable/Hash.h>
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#include <Common/randomSeed.h>
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#include <common/unaligned.h>
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@ -8,11 +9,6 @@
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namespace DB
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{
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// TODO(dakovalkov): remove this workaround.
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#if !defined(__clang__)
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# pragma GCC diagnostic ignored "-Wvector-operation-performance"
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#endif
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DECLARE_MULTITARGET_CODE(
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namespace
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@ -80,250 +76,34 @@ void RandImpl::execute(char * output, size_t size)
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/// It is guaranteed (by PaddedPODArray) that we can overwrite up to 15 bytes after end.
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}
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void RandImpl2::execute(char * output, size_t size)
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{
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if (size == 0)
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return;
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LinearCongruentialGenerator generator0;
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LinearCongruentialGenerator generator1;
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LinearCongruentialGenerator generator2;
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LinearCongruentialGenerator generator3;
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LinearCongruentialGenerator generator4;
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LinearCongruentialGenerator generator5;
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LinearCongruentialGenerator generator6;
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LinearCongruentialGenerator generator7;
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UInt64 rand_seed = randomSeed();
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seed(generator0, rand_seed, 0xfaaae481acb5874aULL + reinterpret_cast<intptr_t>(output));
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seed(generator1, rand_seed, 0x3181a34f32887db6ULL + reinterpret_cast<intptr_t>(output));
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seed(generator2, rand_seed, 0xb6970e4a91b66afdULL + reinterpret_cast<intptr_t>(output));
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seed(generator3, rand_seed, 0xc16062649e83dc13ULL + reinterpret_cast<intptr_t>(output));
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seed(generator4, rand_seed, 0xbb093972da5c8d92ULL + reinterpret_cast<intptr_t>(output));
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seed(generator5, rand_seed, 0xc37dcc410dcfed31ULL + reinterpret_cast<intptr_t>(output));
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seed(generator6, rand_seed, 0x45e1526b7a4367d5ULL + reinterpret_cast<intptr_t>(output));
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seed(generator7, rand_seed, 0x99c2759203868a7fULL + reinterpret_cast<intptr_t>(output));
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const char * end = output + size;
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constexpr int bytes_per_write = 32;
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constexpr int safe_overwrite = 15;
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for (; (end - output) + safe_overwrite >= bytes_per_write; output += safe_overwrite)
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{
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unalignedStore<UInt32>(output, generator0.next());
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unalignedStore<UInt32>(output + 4, generator1.next());
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unalignedStore<UInt32>(output + 8, generator2.next());
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unalignedStore<UInt32>(output + 12, generator3.next());
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unalignedStore<UInt32>(output + 16, generator4.next());
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unalignedStore<UInt32>(output + 20, generator5.next());
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unalignedStore<UInt32>(output + 24, generator6.next());
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unalignedStore<UInt32>(output + 28, generator7.next());
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}
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seed(generator0, rand_seed, 0xfaaae481acb5874aULL + reinterpret_cast<intptr_t>(output));
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seed(generator1, rand_seed, 0x3181a34f32887db6ULL + reinterpret_cast<intptr_t>(output));
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seed(generator2, rand_seed, 0xb6970e4a91b66afdULL + reinterpret_cast<intptr_t>(output));
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seed(generator3, rand_seed, 0xc16062649e83dc13ULL + reinterpret_cast<intptr_t>(output));
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if (end - output > 0)
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{
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unalignedStore<UInt32>(output, generator0.next());
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unalignedStore<UInt32>(output + 4, generator1.next());
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unalignedStore<UInt32>(output + 8, generator2.next());
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unalignedStore<UInt32>(output + 12, generator3.next());
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}
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}
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typedef UInt64 UInt64x16 __attribute__ ((vector_size (128)));
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typedef UInt64 UInt64x8 __attribute__ ((vector_size (64)));
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typedef UInt64 UInt64x4 __attribute__ ((vector_size (32)));
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typedef UInt32 UInt32x16 __attribute__ ((vector_size (64)));
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typedef UInt32 UInt32x8 __attribute__ ((vector_size (32)));
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typedef UInt32 UInt32x4 __attribute__ ((vector_size (16)));
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template <int Size>
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struct DummyStruct;
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template <>
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struct DummyStruct<4>
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{
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using UInt64Type = UInt64x4;
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using UInt32Type = UInt32x4;
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};
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template <>
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struct DummyStruct<8>
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{
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using UInt64Type = UInt64x8;
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using UInt32Type = UInt32x8;
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};
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template <>
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struct DummyStruct<16>
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{
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using UInt64Type = UInt64x16;
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using UInt32Type = UInt32x16;
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};
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template <int Size>
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using VecUInt64 = typename DummyStruct<Size>::UInt64Type;
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template <int Size>
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using VecUInt32 = typename DummyStruct<Size>::UInt32Type;
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void RandImpl3::execute(char * output, size_t size)
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{
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if (size == 0)
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return;
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char * end = output + size;
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UInt64x4 generators = {
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0xfb4121280b2ab902ULL + reinterpret_cast<intptr_t>(output),
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0x0121cf76df39c673ULL + reinterpret_cast<intptr_t>(output),
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0x17ae86e3a19a602fULL + reinterpret_cast<intptr_t>(output),
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0x8b6e16da7e06d622ULL + reinterpret_cast<intptr_t>(output),
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};
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constexpr int bytes_per_write = sizeof(UInt32x4);
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constexpr int safe_overwrite = 15;
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while ((end - output) + safe_overwrite >= bytes_per_write)
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{
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generators *= LinearCongruentialGenerator::a;
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generators += LinearCongruentialGenerator::c;
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unalignedStore<UInt32x4>(output, __builtin_convertvector(generators >> 16, UInt32x4));
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output += bytes_per_write;
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}
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}
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void RandImpl4::execute(char * output, size_t size)
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{
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if (size == 0)
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return;
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char * end = output + size;
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UInt64 rand_seed = randomSeed();
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UInt64x8 generators = {
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calcSeed(rand_seed, 0xfb4121280b2ab902ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x0121cf76df39c673ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x17ae86e3a19a602fULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x8b6e16da7e06d622ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0xfb4121f80b2ab902ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x0122cf767f39c633ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x14ae86e3a79a502fULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x876316da7e06d622ULL + reinterpret_cast<intptr_t>(output)),
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};
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constexpr int bytes_per_write = sizeof(UInt32x8);
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constexpr int safe_overwrite = 15;
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while ((end - output) + safe_overwrite >= bytes_per_write)
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{
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generators *= LinearCongruentialGenerator::a;
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generators += LinearCongruentialGenerator::c;
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unalignedStore<UInt32x8>(output, __builtin_convertvector(generators >> 16, UInt32x8));
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output += bytes_per_write;
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}
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if ((end - output) > 0)
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{
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generators *= LinearCongruentialGenerator::a;
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generators += LinearCongruentialGenerator::c;
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UInt32x8 values = __builtin_convertvector(generators >> 16, UInt32x8);
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for (int i = 0; (end - output) > 0; ++i)
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{
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unalignedStore<UInt32>(output, values[i]);
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output += sizeof(UInt32);
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}
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}
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}
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void RandImpl5::execute(char * output, size_t size)
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{
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if (size == 0)
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return;
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char * end = output + size;
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UInt64 rand_seed = randomSeed();
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UInt64x16 generators = {
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calcSeed(rand_seed, 0xfb4121280b2ab902ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x0121cf76df39c673ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x17ae86e3a19a602fULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x8b6e16da7e06d622ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0xfb4121f80b2ab902ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x0122cf767f39c633ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x14ae86e3a79a502fULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x876316da7e06d622ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0xfb4821280b2ab912ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x0126cf76df39c633ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x17a486e3a19a602fULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x8b6216da7e08d622ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0xfb4101f80b5ab902ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x01226f767f34c633ULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x14ae86e3a75a502fULL + reinterpret_cast<intptr_t>(output)),
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calcSeed(rand_seed, 0x876e36da7e36d622ULL + reinterpret_cast<intptr_t>(output)),
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};
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constexpr int bytes_per_write = sizeof(UInt32x16);
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constexpr int safe_overwrite = 15;
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while ((end - output) + safe_overwrite >= bytes_per_write)
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{
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generators *= LinearCongruentialGenerator::a;
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generators += LinearCongruentialGenerator::c;
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unalignedStore<UInt32x16>(output, __builtin_convertvector(generators >> 16, UInt32x16));
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output += bytes_per_write;
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}
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if ((end - output) > 0)
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{
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generators *= LinearCongruentialGenerator::a;
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generators += LinearCongruentialGenerator::c;
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UInt32x16 values = __builtin_convertvector(generators >> 16, UInt32x16);
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for (int i = 0; (end - output) > 0; ++i)
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{
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unalignedStore<UInt32>(output, values[i]);
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output += sizeof(UInt32);
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}
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}
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}
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namespace {
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constexpr std::array<UInt64, 16> random_numbers = {
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0x0c8ff307dabc0c4cULL,
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0xf4bce78bf3821c1bULL,
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0x4eb628a1e189c21aULL,
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0x85ae000d253e0dbcULL,
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// The array of random numbers from 'head -c8 /dev/urandom | xxd -p'.
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// Can be used for creating seeds for random generators.
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constexpr std::array<UInt64, 32> random_numbers = {
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0x0c8ff307dabc0c4cULL, 0xf4bce78bf3821c1bULL, 0x4eb628a1e189c21aULL, 0x85ae000d253e0dbcULL,
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0xc98073e6480f8a10ULL, 0xb17e9b70a084d570ULL, 0x1361c752b768da8cULL, 0x3d915f60c06d144dULL,
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0xd5bc9b7aced79587ULL, 0x66c28000ba8a66cfULL, 0x0fb58da7a48820f5ULL, 0x540ee1b57aa861a1ULL,
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0x212f11936ef2db04ULL, 0xa3939cd900edcc58ULL, 0xc676c84420170102ULL, 0xcbdc824e8b4bf3edULL,
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0xc98073e6480f8a10ULL,
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0xb17e9b70a084d570ULL,
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0x1361c752b768da8cULL,
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0x3d915f60c06d144dULL,
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0xd5bc9b7aced79587ULL,
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0x66c28000ba8a66cfULL,
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0x0fb58da7a48820f5ULL,
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0x540ee1b57aa861a1ULL,
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0x212f11936ef2db04ULL,
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0xa3939cd900edcc58ULL,
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0xc676c84420170102ULL,
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0xcbdc824e8b4bf3edULL,
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0x8296f9d93cc94e3bULL, 0x78a7e826d62085b2ULL, 0xaa30620211fc6c69ULL, 0xbd38de52f0a93677ULL,
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0x19983de8d79dcc4eULL, 0x8afe883ef2199e6fULL, 0xb7160f7ed022b60aULL, 0x2ce173d373ddafd4ULL,
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0x15762761bb55b9acULL, 0x3e448fc94fdd28e7ULL, 0xa5121232adfbe70aULL, 0xb1e0f6d286112804ULL,
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0x6062e96de9554806ULL, 0xcc679b329c28882aULL, 0x5c6d29f45cbc060eULL, 0x1af1325a86ffb162ULL,
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};
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};
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template <int VectorSize>
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void RandVecImpl<VectorSize>::execute(char * output, size_t size)
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using namespace VectorExtension;
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template <int VecSize>
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void RandVecImpl<VecSize>::execute(char * output, size_t size)
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{
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static_assert(VectorSize >= 4);
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static_assert(VectorSize <= random_numbers.size());
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static_assert(VecSize >= 4);
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static_assert(VecSize <= random_numbers.size());
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using VecUInt64 = UInt64x<VecSize>;
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using VecUInt32 = UInt32x<VecSize>;
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if (size == 0)
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return;
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@ -331,80 +111,38 @@ void RandVecImpl<VectorSize>::execute(char * output, size_t size)
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char * end = output + size;
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constexpr int safe_overwrite = 15;
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constexpr int bytes_per_write = sizeof(VecUInt32<VectorSize>);
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constexpr int bytes_per_write = sizeof(VecUInt32);
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UInt64 rand_seed = randomSeed();
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VecUInt64<VectorSize> generators{};
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for (int i = 0; i < VectorSize; ++i)
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generators[i] = calcSeed(rand_seed, random_numbers[VectorSize] + reinterpret_cast<intptr_t>(output));
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UInt64 a = LinearCongruentialGenerator::a;
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// TODO(dakovalkov): try to remove this.
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/// Note: GCC likes to expand multiplication by a constant into shifts + additions.
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/// In this case a few multiplications become tens of shifts and additions. That leads to a huge slow down.
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/// To avoid it we pretend that 'a' is not a constant. Actually we hope that rand_seed is never 0.
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if (rand_seed == 0)
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a = LinearCongruentialGenerator::a + 2;
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constexpr UInt64 c = LinearCongruentialGenerator::c;
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VecUInt64 generators{};
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for (int i = 0; i < VecSize; ++i)
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generators[i] = calcSeed(rand_seed, random_numbers[i] + reinterpret_cast<intptr_t>(output));
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while ((end - output) + safe_overwrite >= bytes_per_write)
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{
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generators *= LinearCongruentialGenerator::a;
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generators += LinearCongruentialGenerator::c;
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VecUInt32<VectorSize> values = __builtin_convertvector(generators >> 16, VecUInt32<VectorSize>);
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unalignedStore<VecUInt32<VectorSize>>(output, values);
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output += bytes_per_write;
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}
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if ((end - output) > 0)
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{
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generators *= LinearCongruentialGenerator::a;
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generators += LinearCongruentialGenerator::c;
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VecUInt32<VectorSize> values = __builtin_convertvector(generators >> 16, VecUInt32<VectorSize>);
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for (int i = 0; (end - output) > 0; ++i)
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{
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unalignedStore<UInt32>(output, values[i]);
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output += sizeof(UInt32);
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}
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}
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}
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template struct RandVecImpl<4>;
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template struct RandVecImpl<8>;
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template struct RandVecImpl<16>;
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template <int VectorSize>
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void RandVecImpl2<VectorSize>::execute(char * output, size_t size)
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{
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static_assert(VectorSize >= 4);
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if (size == 0)
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return;
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char * end = output + size;
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constexpr int safe_overwrite = 15;
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constexpr int bytes_per_write = 2 * sizeof(VecUInt32<VectorSize>);
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UInt64 rand_seed = randomSeed();
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VecUInt64<VectorSize> gens1{}, gens2{};
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for (int i = 0; i < VectorSize; ++i)
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{
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gens1[i] = calcSeed(rand_seed, i * 1123465ull * reinterpret_cast<intptr_t>(output));
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gens2[i] = calcSeed(rand_seed, i * 6432453ull * reinterpret_cast<intptr_t>(output));
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}
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while ((end - output) + safe_overwrite >= bytes_per_write)
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{
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gens1 *= LinearCongruentialGenerator::a;
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gens1 += LinearCongruentialGenerator::c;
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VecUInt32<VectorSize> values1 = __builtin_convertvector(gens1 >> 16, VecUInt32<VectorSize>);
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unalignedStore<VecUInt32<VectorSize>>(output, values1);
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gens2 *= LinearCongruentialGenerator::a;
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gens2 += LinearCongruentialGenerator::c;
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VecUInt32<VectorSize> values2 = __builtin_convertvector(gens2 >> 16, VecUInt32<VectorSize>);
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unalignedStore<VecUInt32<VectorSize>>(output, values2);
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generators = generators * a + c;;
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VecUInt32 values = __builtin_convertvector(generators >> 16, VecUInt32);
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unalignedStore<VecUInt32>(output, values);
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output += bytes_per_write;
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}
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// Process tail
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while ((end - output) > 0)
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{
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gens1 *= LinearCongruentialGenerator::a;
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gens1 += LinearCongruentialGenerator::c;
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VecUInt32<VectorSize> values = __builtin_convertvector(gens1 >> 16, VecUInt32<VectorSize>);
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for (int i = 0; (end - output) > 0 && i < VectorSize; ++i)
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generators = generators * a + c;;
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VecUInt32 values = __builtin_convertvector(generators >> 16, VecUInt32);
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for (int i = 0; i < VecSize && (end - output) > 0; ++i)
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{
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||||
unalignedStore<UInt32>(output, values[i]);
|
||||
output += sizeof(UInt32);
|
||||
@ -412,144 +150,147 @@ void RandVecImpl2<VectorSize>::execute(char * output, size_t size)
|
||||
}
|
||||
}
|
||||
|
||||
template struct RandVecImpl2<4>;
|
||||
template struct RandVecImpl2<8>;
|
||||
template struct RandVecImpl2<16>;
|
||||
template <int VecSize>
|
||||
void RandVecImpl2<VecSize>::execute(char * output, size_t size)
|
||||
{
|
||||
static_assert(VecSize >= 4);
|
||||
static_assert(2 * VecSize <= random_numbers.size());
|
||||
|
||||
// template <int VectorSize>
|
||||
// void RandVecImpl4<VectorSize>::execute(char * output, size_t size)
|
||||
// {
|
||||
// static_assert(VectorSize >= 4);
|
||||
using VecUInt64 = UInt64x<VecSize>;
|
||||
using VecUInt32 = UInt32x<VecSize>;
|
||||
|
||||
// if (size == 0)
|
||||
// return;
|
||||
if (size == 0)
|
||||
return;
|
||||
|
||||
// char * end = output + size;
|
||||
char * end = output + size;
|
||||
|
||||
// constexpr int safe_overwrite = 15;
|
||||
// constexpr int bytes_per_write = 4 * sizeof(VecUInt32<VectorSize>);
|
||||
constexpr int safe_overwrite = 15;
|
||||
constexpr int bytes_per_write = 2 * sizeof(VecUInt32);
|
||||
|
||||
// VecUInt64<VectorSize> gens1{}, gens2{}, gens3{}, gens4{};
|
||||
// for (int i = 0; i < VectorSize; ++i)
|
||||
// {
|
||||
// gens1[i] = calcSeed(i * 1123465ull * reinterpret_cast<intptr_t>(output));
|
||||
// gens2[i] = calcSeed(i * 6432453ull * reinterpret_cast<intptr_t>(output));
|
||||
// gens3[i] = calcSeed(i * 1346434ull * reinterpret_cast<intptr_t>(output));
|
||||
// gens4[i] = calcSeed(i * 5344753ull * reinterpret_cast<intptr_t>(output));
|
||||
// }
|
||||
UInt64 rand_seed = randomSeed();
|
||||
|
||||
// while ((end - output) + safe_overwrite >= bytes_per_write)
|
||||
// {
|
||||
// gens1 *= LinearCongruentialGenerator::a;
|
||||
// gens1 += LinearCongruentialGenerator::c;
|
||||
// VecUInt32<VectorSize> values1 = __builtin_convertvector(gens1 >> 16, VecUInt32<VectorSize>);
|
||||
// unalignedStore<VecUInt32<VectorSize>>(output, values1);
|
||||
// gens2 *= LinearCongruentialGenerator::a;
|
||||
// gens2 += LinearCongruentialGenerator::c;
|
||||
// VecUInt32<VectorSize> values2 = __builtin_convertvector(gens2 >> 16, VecUInt32<VectorSize>);
|
||||
// unalignedStore<VecUInt32<VectorSize>>(output, values2);
|
||||
// gens3 *= LinearCongruentialGenerator::a;
|
||||
// gens3 += LinearCongruentialGenerator::c;
|
||||
// VecUInt32<VectorSize> values3 = __builtin_convertvector(gens3 >> 16, VecUInt32<VectorSize>);
|
||||
// unalignedStore<VecUInt32<VectorSize>>(output, values3);
|
||||
// gens4 *= LinearCongruentialGenerator::a;
|
||||
// gens4 += LinearCongruentialGenerator::c;
|
||||
// VecUInt32<VectorSize> values4 = __builtin_convertvector(gens4 >> 16, VecUInt32<VectorSize>);
|
||||
// unalignedStore<VecUInt32<VectorSize>>(output, values4);
|
||||
// output += bytes_per_write;
|
||||
// }
|
||||
UInt64 a = LinearCongruentialGenerator::a;
|
||||
// TODO(dakovalkov): try to remove this.
|
||||
/// Note: GCC likes to expand multiplication by a constant into shifts + additions.
|
||||
/// In this case a few multiplications become tens of shifts and additions. That leads to a huge slow down.
|
||||
/// To avoid it we pretend that 'a' is not a constant. Actually we hope that rand_seed is never 0.
|
||||
if (rand_seed == 0)
|
||||
a = LinearCongruentialGenerator::a + 2;
|
||||
|
||||
// while ((end - output) > 0)
|
||||
// {
|
||||
// gens1 *= LinearCongruentialGenerator::a;
|
||||
// gens1 += LinearCongruentialGenerator::c;
|
||||
// VecUInt32<VectorSize> values = __builtin_convertvector(gens1 >> 16, VecUInt32<VectorSize>);
|
||||
// for (int i = 0; (end - output) > 0 && i < VectorSize; i += 4)
|
||||
// {
|
||||
// unalignedStore<UInt32>(output, values[i]);
|
||||
// unalignedStore<UInt32>(output + 4, values[i + 1]);
|
||||
// unalignedStore<UInt32>(output + 8, values[i + 2]);
|
||||
// unalignedStore<UInt32>(output + 12, values[i + 3]);
|
||||
// output += 16;
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
constexpr UInt64 c = LinearCongruentialGenerator::c;
|
||||
|
||||
// template struct RandVecImpl2<4>;
|
||||
// template struct RandVecImpl2<8>;
|
||||
// template struct RandVecImpl2<16>;
|
||||
VecUInt64 gens1{};
|
||||
VecUInt64 gens2{};
|
||||
for (int i = 0; i < VecSize; ++i)
|
||||
{
|
||||
gens1[i] = calcSeed(rand_seed, random_numbers[i] + reinterpret_cast<intptr_t>(output));
|
||||
gens2[i] = calcSeed(rand_seed, random_numbers[i + VecSize] + reinterpret_cast<intptr_t>(output));
|
||||
}
|
||||
|
||||
while ((end - output) + safe_overwrite >= bytes_per_write)
|
||||
{
|
||||
gens1 = gens1 * a + c;;
|
||||
VecUInt32 values1 = __builtin_convertvector(gens1 >> 16, VecUInt32);
|
||||
unalignedStore<VecUInt32>(output, values1);
|
||||
gens2 = gens2 * a + c;;
|
||||
VecUInt32 values2 = __builtin_convertvector(gens2 >> 16, VecUInt32);
|
||||
unalignedStore<VecUInt32>(output + sizeof(VecUInt32), values2);
|
||||
output += bytes_per_write;
|
||||
}
|
||||
|
||||
// Process tail
|
||||
while ((end - output) > 0)
|
||||
{
|
||||
gens1 = gens1 * a + c;;
|
||||
VecUInt32 values = __builtin_convertvector(gens1 >> 16, VecUInt32);
|
||||
for (int i = 0; i < VecSize && (end - output) > 0; ++i)
|
||||
{
|
||||
unalignedStore<UInt32>(output, values[i]);
|
||||
output += sizeof(UInt32);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template <int VecSize>
|
||||
void RandVecImpl4<VecSize>::execute(char * output, size_t size)
|
||||
{
|
||||
static_assert(VecSize >= 4);
|
||||
static_assert(4 * VecSize <= random_numbers.size());
|
||||
|
||||
using VecUInt64 = UInt64x<VecSize>;
|
||||
using VecUInt32 = UInt32x<VecSize>;
|
||||
|
||||
if (size == 0)
|
||||
return;
|
||||
|
||||
char * end = output + size;
|
||||
|
||||
constexpr int safe_overwrite = 15;
|
||||
constexpr int bytes_per_write = 4 * sizeof(VecUInt32);
|
||||
|
||||
UInt64 rand_seed = randomSeed();
|
||||
|
||||
UInt64 a = LinearCongruentialGenerator::a;
|
||||
// TODO(dakovalkov): try to remove this.
|
||||
/// Note: GCC likes to expand multiplication by a constant into shifts + additions.
|
||||
/// In this case a few multiplications become tens of shifts and additions. That leads to a huge slow down.
|
||||
/// To avoid it we pretend that 'a' is not a constant. Actually we hope that rand_seed is never 0.
|
||||
if (rand_seed == 0)
|
||||
a = LinearCongruentialGenerator::a + 2;
|
||||
|
||||
constexpr UInt64 c = LinearCongruentialGenerator::c;
|
||||
|
||||
VecUInt64 gens1{};
|
||||
VecUInt64 gens2{};
|
||||
VecUInt64 gens3{};
|
||||
VecUInt64 gens4{};
|
||||
for (int i = 0; i < VecSize; ++i)
|
||||
{
|
||||
gens1[i] = calcSeed(rand_seed, random_numbers[i] + reinterpret_cast<intptr_t>(output));
|
||||
gens2[i] = calcSeed(rand_seed, random_numbers[i + VecSize] + reinterpret_cast<intptr_t>(output));
|
||||
gens3[i] = calcSeed(rand_seed, random_numbers[i + 2 * VecSize] + reinterpret_cast<intptr_t>(output));
|
||||
gens4[i] = calcSeed(rand_seed, random_numbers[i + 3 * VecSize] + reinterpret_cast<intptr_t>(output));
|
||||
}
|
||||
|
||||
while ((end - output) + safe_overwrite >= bytes_per_write)
|
||||
{
|
||||
gens1 = gens1 * a + c;
|
||||
VecUInt32 values1 = __builtin_convertvector(gens1 >> 16, VecUInt32);
|
||||
unalignedStore<VecUInt32>(output, values1);
|
||||
gens2 = gens2 * a + c;
|
||||
VecUInt32 values2 = __builtin_convertvector(gens2 >> 16, VecUInt32);
|
||||
unalignedStore<VecUInt32>(output + sizeof(VecUInt32), values2);
|
||||
gens3 = gens3 * a + c;
|
||||
VecUInt32 values3 = __builtin_convertvector(gens3 >> 16, VecUInt32);
|
||||
unalignedStore<VecUInt32>(output + 2 * sizeof(VecUInt32), values3);
|
||||
gens4 = gens4 * a + c;
|
||||
VecUInt32 values4 = __builtin_convertvector(gens4 >> 16, VecUInt32);
|
||||
unalignedStore<VecUInt32>(output + 3 * sizeof(VecUInt32), values4);
|
||||
output += bytes_per_write;
|
||||
}
|
||||
|
||||
// Process tail
|
||||
while ((end - output) > 0)
|
||||
{
|
||||
gens1 = gens1 * a + c;;
|
||||
VecUInt32 values = __builtin_convertvector(gens1 >> 16, VecUInt32);
|
||||
for (int i = 0; i < VecSize && (end - output) > 0; ++i)
|
||||
{
|
||||
unalignedStore<UInt32>(output, values[i]);
|
||||
output += sizeof(UInt32);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
) // DECLARE_MULTITARGET_CODE
|
||||
|
||||
DECLARE_AVX2_SPECIFIC_CODE(
|
||||
|
||||
void RandImpl6::execute(char * output, size_t size)
|
||||
{
|
||||
if (size == 0)
|
||||
return;
|
||||
|
||||
char * end = output + size;
|
||||
|
||||
UInt64x8 generators = {
|
||||
0x5f186ce5faee450bULL + reinterpret_cast<intptr_t>(output),
|
||||
0x9adb2ca3c72ac2eeULL + reinterpret_cast<intptr_t>(output),
|
||||
0x07acf8bfa2537705ULL + reinterpret_cast<intptr_t>(output),
|
||||
0x692b1b533834db92ULL + reinterpret_cast<intptr_t>(output),
|
||||
0x5148b84cdda30081ULL + reinterpret_cast<intptr_t>(output),
|
||||
0xe17b8a75a301ad47ULL + reinterpret_cast<intptr_t>(output),
|
||||
0x6d4a5d69ed2a5f56ULL + reinterpret_cast<intptr_t>(output),
|
||||
0x114e23266201b333ULL + reinterpret_cast<intptr_t>(output),
|
||||
};
|
||||
|
||||
union {
|
||||
UInt64x8 vec;
|
||||
__m256i mm[2];
|
||||
} gens {generators};
|
||||
|
||||
constexpr int bytes_per_write = sizeof(UInt32x8);
|
||||
constexpr int safe_overwrite = 15;
|
||||
|
||||
const auto low_a = _mm256_set1_epi64x(0xDEECE66D);
|
||||
// const auto high_a = _mm256_set1_epi64x(5);
|
||||
const auto c = _mm256_set1_epi64x(11);
|
||||
|
||||
while ((end - output) + safe_overwrite >= bytes_per_write)
|
||||
{
|
||||
{
|
||||
auto gens_high = _mm256_srli_epi64(gens.mm[0], 32);
|
||||
auto low_low_res = _mm256_mul_epu32(gens.mm[0], low_a);
|
||||
auto high_low_res = _mm256_slli_epi64(_mm256_mul_epu32(gens_high, low_a), 32);
|
||||
auto low_high_res = _mm256_slli_epi64(gens.mm[0], 32) + _mm256_slli_epi64(gens.mm[0], 34);
|
||||
gens.mm[0] = _mm256_add_epi64(_mm256_add_epi64(low_low_res, high_low_res),
|
||||
_mm256_add_epi64(low_high_res, c));
|
||||
}
|
||||
{
|
||||
auto gens_high = _mm256_srli_epi64(gens.mm[1], 32);
|
||||
auto low_low_res = _mm256_mul_epu32(gens.mm[1], low_a);
|
||||
auto high_low_res = _mm256_slli_epi64(_mm256_mul_epu32(gens_high, low_a), 32);
|
||||
auto low_high_res = _mm256_slli_epi64(gens.mm[1], 32) + _mm256_slli_epi64(gens.mm[1], 34);
|
||||
gens.mm[1] = _mm256_add_epi64(_mm256_add_epi64(low_low_res, high_low_res),
|
||||
_mm256_add_epi64(low_high_res, c));
|
||||
}
|
||||
// generators *= LinearCongruentialGenerator::a;
|
||||
// generators += LinearCongruentialGenerator::c;
|
||||
unalignedStore<UInt32x8>(output, __builtin_convertvector(gens.vec >> 16, UInt32x8));
|
||||
output += bytes_per_write;
|
||||
}
|
||||
|
||||
if ((end - output) > 0)
|
||||
{
|
||||
generators *= LinearCongruentialGenerator::a;
|
||||
generators += LinearCongruentialGenerator::c;
|
||||
UInt32x8 values = __builtin_convertvector(generators >> 16, UInt32x8);
|
||||
for (int i = 0; (end - output) > 0; ++i)
|
||||
{
|
||||
unalignedStore<UInt32>(output, values[i]);
|
||||
output += sizeof(UInt32);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
template struct RandVecImpl4<4>;
|
||||
) // DECLARE_AVX2_SPECIFIC_CODE
|
||||
|
||||
DECLARE_AVX512F_SPECIFIC_CODE(
|
||||
template struct RandVecImpl4<8>;
|
||||
) // DECLARE_AVX512F_SPECIFIC_CODE
|
||||
|
||||
|
||||
}
|
||||
|
||||
@ -43,49 +43,26 @@ struct RandImpl
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch); }
|
||||
};
|
||||
|
||||
struct RandImpl2
|
||||
{
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_v2"; }
|
||||
};
|
||||
|
||||
struct RandImpl3
|
||||
{
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_v3"; }
|
||||
};
|
||||
|
||||
struct RandImpl4
|
||||
{
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_v4"; }
|
||||
};
|
||||
|
||||
struct RandImpl5
|
||||
{
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_v5"; }
|
||||
};
|
||||
|
||||
template <int VectorSize>
|
||||
// Isn't used now.
|
||||
template <int VecSize>
|
||||
struct RandVecImpl
|
||||
{
|
||||
static void execute(char * outpu, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_vec_" + toString(VectorSize); }
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_vec_" + toString(VecSize); }
|
||||
};
|
||||
|
||||
template <int VectorSize>
|
||||
// Isn't used now.
|
||||
template <int VecSize>
|
||||
struct RandVecImpl2
|
||||
{
|
||||
static void execute(char * outpu, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_vec2_" + toString(VectorSize); }
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_vec2_" + toString(VecSize); }
|
||||
};
|
||||
|
||||
struct RandImpl6
|
||||
template <int VecSize>
|
||||
struct RandVecImpl4
|
||||
{
|
||||
static void execute(char * outpu, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_v6"; }
|
||||
static void execute(char * output, size_t size);
|
||||
static String getImplementationTag() { return ToString(BuildArch) + "_vec4_" + toString(VecSize); }
|
||||
};
|
||||
|
||||
) // DECLARE_MULTITARGET_CODE
|
||||
@ -144,72 +121,16 @@ public:
|
||||
{
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandImpl, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandImpl2, ToType, Name>>();
|
||||
|
||||
if constexpr (UseMultitargetCode)
|
||||
{
|
||||
selector.registerImplementation<TargetArch::SSE42,
|
||||
FunctionRandomImpl<TargetSpecific::SSE42::RandImpl, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX,
|
||||
FunctionRandomImpl<TargetSpecific::AVX::RandImpl, ToType, Name>>();
|
||||
// vec impl 4
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandImpl, ToType, Name>>();
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandVecImpl4<4>, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::AVX512F,
|
||||
FunctionRandomImpl<TargetSpecific::AVX512F::RandImpl, ToType, Name>>();
|
||||
FunctionRandomImpl<TargetSpecific::AVX512F::RandVecImpl4<8>, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandImpl2, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandImpl3, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandImpl3, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandImpl4, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandImpl4, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandImpl5, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandImpl5, ToType, Name>>();
|
||||
|
||||
// vec impl
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandVecImpl<4>, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandVecImpl<4>, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandVecImpl<8>, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandVecImpl<8>, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandVecImpl<16>, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandVecImpl<16>, ToType, Name>>();
|
||||
|
||||
// vec impl 2
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandVecImpl2<4>, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandVecImpl2<4>, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandVecImpl2<8>, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandVecImpl2<8>, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::Default,
|
||||
FunctionRandomImpl<TargetSpecific::Default::RandVecImpl2<16>, ToType, Name>>();
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandVecImpl2<16>, ToType, Name>>();
|
||||
|
||||
selector.registerImplementation<TargetArch::AVX2,
|
||||
FunctionRandomImpl<TargetSpecific::AVX2::RandImpl6, ToType, Name>>();
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
101
src/Functions/VectorExtension.h
Normal file
101
src/Functions/VectorExtension.h
Normal file
@ -0,0 +1,101 @@
|
||||
#pragma once
|
||||
|
||||
#include <Core/Types.h>
|
||||
// Contains types declarations and wrappers for GCC vector extension.
|
||||
|
||||
// TODO(dakovalkov): remove this workaround.
|
||||
#if !defined(__clang__)
|
||||
# pragma GCC diagnostic ignored "-Wvector-operation-performance"
|
||||
#endif
|
||||
|
||||
namespace DB::VectorExtension
|
||||
{
|
||||
|
||||
typedef UInt64 UInt64x2 __attribute__ ((vector_size (sizeof(UInt64) * 2)));
|
||||
typedef UInt64 UInt64x4 __attribute__ ((vector_size (sizeof(UInt64) * 4)));
|
||||
typedef UInt64 UInt64x8 __attribute__ ((vector_size (sizeof(UInt64) * 8)));
|
||||
typedef UInt64 UInt64x16 __attribute__ ((vector_size (sizeof(UInt64) * 16)));
|
||||
typedef UInt64 UInt64x32 __attribute__ ((vector_size (sizeof(UInt64) * 32)));
|
||||
|
||||
typedef UInt32 UInt32x2 __attribute__ ((vector_size (sizeof(UInt32) * 2)));
|
||||
typedef UInt32 UInt32x4 __attribute__ ((vector_size (sizeof(UInt32) * 4)));
|
||||
typedef UInt32 UInt32x8 __attribute__ ((vector_size (sizeof(UInt32) * 8)));
|
||||
typedef UInt32 UInt32x16 __attribute__ ((vector_size (sizeof(UInt32) * 16)));
|
||||
typedef UInt32 UInt32x32 __attribute__ ((vector_size (sizeof(UInt32) * 32)));
|
||||
typedef UInt32 UInt32x64 __attribute__ ((vector_size (sizeof(UInt32) * 64)));
|
||||
|
||||
typedef UInt16 UInt16x2 __attribute__ ((vector_size (sizeof(UInt16) * 2)));
|
||||
typedef UInt16 UInt16x4 __attribute__ ((vector_size (sizeof(UInt16) * 4)));
|
||||
typedef UInt16 UInt16x8 __attribute__ ((vector_size (sizeof(UInt16) * 8)));
|
||||
typedef UInt16 UInt16x16 __attribute__ ((vector_size (sizeof(UInt16) * 16)));
|
||||
typedef UInt16 UInt16x32 __attribute__ ((vector_size (sizeof(UInt16) * 32)));
|
||||
typedef UInt16 UInt16x64 __attribute__ ((vector_size (sizeof(UInt16) * 64)));
|
||||
|
||||
typedef UInt8 UInt8x2 __attribute__ ((vector_size (sizeof(UInt8) * 2)));
|
||||
typedef UInt8 UInt8x4 __attribute__ ((vector_size (sizeof(UInt8) * 4)));
|
||||
typedef UInt8 UInt8x8 __attribute__ ((vector_size (sizeof(UInt8) * 8)));
|
||||
typedef UInt8 UInt8x16 __attribute__ ((vector_size (sizeof(UInt8) * 16)));
|
||||
typedef UInt8 UInt8x32 __attribute__ ((vector_size (sizeof(UInt8) * 32)));
|
||||
typedef UInt8 UInt8x64 __attribute__ ((vector_size (sizeof(UInt8) * 64)));
|
||||
|
||||
namespace detail
|
||||
{
|
||||
template <int Size>
|
||||
struct DummyStruct;
|
||||
|
||||
template <>
|
||||
struct DummyStruct<4>
|
||||
{
|
||||
using UInt8Type = UInt8x4;
|
||||
using UInt16Type = UInt16x4;
|
||||
using UInt32Type = UInt32x4;
|
||||
using UInt64Type = UInt64x4;
|
||||
};
|
||||
template <>
|
||||
struct DummyStruct<8>
|
||||
{
|
||||
using UInt8Type = UInt8x8;
|
||||
using UInt16Type = UInt16x8;
|
||||
using UInt32Type = UInt32x8;
|
||||
using UInt64Type = UInt64x8;
|
||||
};
|
||||
template <>
|
||||
struct DummyStruct<16>
|
||||
{
|
||||
using UInt8Type = UInt8x16;
|
||||
using UInt16Type = UInt16x16;
|
||||
using UInt32Type = UInt32x16;
|
||||
using UInt64Type = UInt64x16;
|
||||
};
|
||||
template <>
|
||||
struct DummyStruct<32>
|
||||
{
|
||||
using UInt8Type = UInt8x32;
|
||||
using UInt16Type = UInt16x32;
|
||||
using UInt32Type = UInt32x32;
|
||||
using UInt64Type = UInt64x32;
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
// Same as above via template, e.g. UInt64x<8>
|
||||
template <int Size>
|
||||
using UInt8x = typename detail::DummyStruct<Size>::UInt8Type;
|
||||
template <int Size>
|
||||
using UInt16x = typename detail::DummyStruct<Size>::UInt16Type;
|
||||
template <int Size>
|
||||
using UInt32x = typename detail::DummyStruct<Size>::UInt32Type;
|
||||
template <int Size>
|
||||
using UInt64x = typename detail::DummyStruct<Size>::UInt64Type;
|
||||
|
||||
/* Casts vectors of the same size.
|
||||
* UInt32x4 x{};
|
||||
* UInt64x4 y = ConvertVector<UInt64x4>(x);
|
||||
*/
|
||||
// template <typename To, typename From>
|
||||
// inline To ConvertVector(From a)
|
||||
// {
|
||||
// return __builtin_convertvector(a, To);
|
||||
// }
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user