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Commit bdbc0eaa authored by Chao Liu's avatar Chao Liu
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cleaning up dead code

parent 7c098ddc
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Showing with 6 additions and 670 deletions
driver/device_implicit_gemm_convolution_2_chwn_cyxk_khwn.hpp
View file @ bdbc0eaa
...@@ -221,7 +221,7 @@ void device_implicit_gemm_convolution_2_chwn_cyxk_khwn(InDesc, ...@@ -221,7 +221,7 @@ void device_implicit_gemm_convolution_2_chwn_cyxk_khwn(InDesc,
constexpr index_t BlockSize = 128; constexpr index_t BlockSize = 128;
#elif 0 #elif 0
// 1x1, 14x14, Vega 20, hack CPerBlock = 1 // 1x1, 14x14, Vega 20, hack CPerBlock = 1 for debugging
constexpr index_t BPerBlock = 64; constexpr index_t BPerBlock = 64;
constexpr index_t KPerBlock = 128; constexpr index_t KPerBlock = 128;
constexpr index_t CPerBlock = 1; constexpr index_t CPerBlock = 1;
......
driver/driver.hip.cpp
View file @ bdbc0eaa
...@@ -580,7 +580,7 @@ int main(int argc, char* argv[]) ...@@ -580,7 +580,7 @@ int main(int argc, char* argv[])
constexpr index_t HPad = 0; constexpr index_t HPad = 0;
constexpr index_t WPad = 0; constexpr index_t WPad = 0;
#elif 1 #elif 0
// 1x1 filter, 14x14 image, C = 2048 // 1x1 filter, 14x14 image, C = 2048
constexpr index_t N = 128; constexpr index_t N = 128;
constexpr index_t C = 2048; constexpr index_t C = 2048;
......
src/include/blockwise_batched_gemm.hip.hpp
View file @ bdbc0eaa
#pragma once #pragma once
#include "threadwise_gemm.hip.hpp" #include "threadwise_gemm.hip.hpp"
template <index_t BlockSize,
class BlockMatrixA,
class BlockMatrixB,
class ThreadMatrixC,
bool TransA,
bool TransB,
bool TransC,
index_t BlockMatrixStrideA,
index_t BlockMatrixStrideB,
index_t ThreadMatrixStrideC,
index_t BatchSize,
index_t BatchPerThread,
index_t KPerThreadLoop,
bool DistributeThreadAlongColumnFirst>
struct Blockwise1dStridedBatchedGemmBlockABlockBThreadC
{
index_t mMyThreadOffsetA = 0;
index_t mMyThreadOffsetB = 0;
struct MatrixIndex
{
index_t batch;
index_t row;
index_t col;
};
__device__ Blockwise1dStridedBatchedGemmBlockABlockBThreadC()
{
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
const auto c_thread_mtx_index = GetBeginOfThreadMatrixC(get_thread_local_1d_id());
mMyThreadOffsetA = c_thread_mtx_index.batch * BlockMatrixStrideA +
((!TransA) ? a_block_mtx.Get1dIndex(c_thread_mtx_index.row, 0)
: a_block_mtx.Get1dIndex(0, c_thread_mtx_index.row));
mMyThreadOffsetB = c_thread_mtx_index.batch * BlockMatrixStrideB +
((!TransB) ? b_block_mtx.Get1dIndex(0, c_thread_mtx_index.col)
: b_block_mtx.Get1dIndex(c_thread_mtx_index.col, 0));
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantMatrixDescriptor(BlockMatrixA{}, "a_block_mtx: ");
print_ConstantMatrixDescriptor(BlockMatrixB{}, "b_block_mtx: ");
print_ConstantMatrixDescriptor(ThreadMatrixC{}, "c_thread_mtx: ");
printf("%u %u, %u %u %u, %u %u\n",
get_block_1d_id(),
get_thread_local_1d_id(),
c_thread_mtx_index.batch,
c_thread_mtx_index.row,
c_thread_mtx_index.col,
mMyThreadOffsetA,
mMyThreadOffsetB);
}
#endif
}
__device__ MatrixIndex GetBeginOfThreadMatrixC(index_t thread_id) const
{
if(TransA && (!TransB) && (!TransC))
{
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
static_assert(a_block_mtx.NRow() == b_block_mtx.NRow(),
"wrong! k dimension not consistent!");
constexpr index_t MPerBlock = a_block_mtx.NCol();
constexpr index_t NPerBlock = b_block_mtx.NCol();
constexpr auto c_thread_mtx = ThreadMatrixC{};
// divide thread work
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
static_assert(BatchSize % BatchPerThread == 0, "BatchSize % BatchPerThread != 0");
static_assert(MPerBlock % MPerThread == 0, "MPerBlock % MPerThread != 0");
static_assert(NPerBlock % NPerThread == 0, "NPerBlock % NPerThread != 0");
constexpr index_t BatchThreadWork = (BatchSize + BatchPerThread - 1) / BatchPerThread;
constexpr index_t MThreadWork = (MPerBlock + MPerThread - 1) / MPerThread;
constexpr index_t NThreadWork = (NPerBlock + NPerThread - 1) / NPerThread;
static_assert(BlockSize == BatchThreadWork * MThreadWork * NThreadWork,
"wrong! wrong BlockSize");
if(DistributeThreadAlongColumnFirst)
{
// num of operations can be reduced
const index_t b_work_id = thread_id / (MThreadWork * NThreadWork);
index_t itmp = thread_id - b_work_id * (MThreadWork * NThreadWork);
const index_t m_work_id = itmp / NThreadWork;
const index_t n_work_id = itmp - m_work_id * NThreadWork;
return MatrixIndex{
b_work_id * BatchPerThread, m_work_id * MPerThread, n_work_id * NPerThread};
}
else
{
// not implemented
assert(false);
}
}
else
{
// not implemented
assert(false);
}
}
// this should be optimized away if input is known
__device__ static MatrixIndex
GetDistanceFromBeginOfThreadMatrixC(index_t batch_in_c, index_t m_in_c, index_t n_in_c)
{
return MatrixIndex{batch_in_c, m_in_c, n_in_c};
}
template <class FloatA, class FloatB, class FloatC, class Accumulator>
__device__ void Run(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread,
Accumulator f_accum) const
{
if(TransA && (!TransB) && (!TransC))
{
constexpr auto True = integral_constant<bool, true>{};
constexpr auto False = integral_constant<bool, false>{};
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
constexpr auto c_thread_mtx = ThreadMatrixC{};
constexpr index_t KPerBlock = a_block_mtx.NRow(); // A is transposed
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
// a is transposed, b is not
constexpr auto a_thread_mtx =
make_ConstantMatrixDescriptor(Number<KPerThreadLoop>{}, Number<MPerThread>{});
constexpr auto b_thread_mtx =
make_ConstantMatrixDescriptor(Number<KPerThreadLoop>{}, Number<NPerThread>{});
FloatA p_a_thread[a_thread_mtx.GetElementSpace()];
FloatB p_b_thread[b_thread_mtx.GetElementSpace()];
// loop over k
for(index_t k_begin = 0; k_begin < KPerBlock; k_begin += KPerThreadLoop)
{
// read first batch of a, b
threadwise_matrix_copy(a_block_mtx,
p_a_block + mMyThreadOffsetA +
k_begin * a_block_mtx.RowStride(),
a_thread_mtx,
p_a_thread,
a_thread_mtx.GetLengths());
threadwise_matrix_copy(b_block_mtx,
p_b_block + mMyThreadOffsetB +
k_begin * b_block_mtx.RowStride(),
b_thread_mtx,
p_b_thread,
b_thread_mtx.GetLengths());
// loop over batch
for(index_t ib = 0; ib + 1 < BatchPerThread; ++ib)
{
// do current batch of gemm
threadwise_gemm(a_thread_mtx,
True,
p_a_thread,
b_thread_mtx,
False,
p_b_thread,
c_thread_mtx,
False,
p_c_thread + ib * ThreadMatrixStrideC,
f_accum);
// read next batch of a, b
if(BlockMatrixStrideA != 0)
{
threadwise_matrix_copy(a_block_mtx,
p_a_block + mMyThreadOffsetA +
(ib + 1) * BlockMatrixStrideA +
+k_begin * a_block_mtx.RowStride(),
a_thread_mtx,
p_a_thread,
a_thread_mtx.GetLengths());
}
if(BlockMatrixStrideB != 0)
{
threadwise_matrix_copy(b_block_mtx,
p_b_block + mMyThreadOffsetB +
(ib + 1) * BlockMatrixStrideB +
k_begin * b_block_mtx.RowStride(),
b_thread_mtx,
p_b_thread,
b_thread_mtx.GetLengths());
}
}
// do last batch of gemm
threadwise_gemm(a_thread_mtx,
True,
p_a_thread,
b_thread_mtx,
False,
p_b_thread,
c_thread_mtx,
False,
p_c_thread + (BatchPerThread - 1) * ThreadMatrixStrideC,
f_accum);
}
}
}
};
template <index_t BlockSize, template <index_t BlockSize,
class BlockMatrixA, class BlockMatrixA,
class BlockMatrixB, class BlockMatrixB,
...@@ -526,236 +301,6 @@ struct BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2 ...@@ -526,236 +301,6 @@ struct BlockwiseBatchGemmBlockABlockBThreadCTransANormalBNormalC_V2
} }
} }
template <class FloatA, class FloatB, class FloatC, class Accumulator>
__device__ void Run_v3(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread,
Accumulator f_accum) const
{
constexpr auto True = integral_constant<bool, true>{};
constexpr auto False = integral_constant<bool, false>{};
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
constexpr auto c_thread_mtx = ThreadMatrixC{};
constexpr index_t KPerBlock = a_block_mtx.NRow(); // A is transposed
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
// thread A, B for GEMM
// A is transposed, b is not
constexpr auto a_thread_mtx =
make_ConstantMatrixDescriptor(Number<KPerThreadLoop>{}, Number<MPerThread>{});
constexpr auto b_thread_mtx =
make_ConstantMatrixDescriptor(Number<KPerThreadLoop>{}, Number<NPerThread>{});
// thread A-sub, B-sub for copy
constexpr auto a_thread_sub_mtx = make_ConstantMatrixDescriptor(
Number<KPerThreadLoop>{}, Number<MPerThreadSubC>{}, Number<MPerThread>{});
constexpr auto b_thread_sub_mtx = make_ConstantMatrixDescriptor(
Number<KPerThreadLoop>{}, Number<NPerThreadSubC>{}, Number<NPerThread>{});
FloatA p_a_thread[a_thread_mtx.GetElementSpace()];
FloatB p_b_thread[b_thread_mtx.GetElementSpace()];
constexpr index_t MPerLevel1Cluster = MPerThreadSubC * MLevel0Cluster * MLevel1Cluster;
constexpr index_t NPerLevel1Cluster = NPerThreadSubC * NLevel0Cluster * NLevel1Cluster;
constexpr index_t MRepeat = MPerThread / MPerThreadSubC;
constexpr index_t NRepeat = NPerThread / NPerThreadSubC;
// loop over k
//#pragma unroll
for(index_t k_begin = 0; k_begin < KPerBlock; k_begin += KPerThreadLoop)
{
// read first batch of A, B
// copy A-sub to form A
//#pragma unroll
for(index_t m_repeat = 0; m_repeat < MRepeat; ++m_repeat)
{
for(index_t i = 0; i < a_thread_sub_mtx.NRow(); ++i)
{
#if 1
for(index_t j = 0; j < a_thread_sub_mtx.NCol(); ++j)
{
p_a_thread[a_thread_mtx.Get1dIndex(i, m_repeat * MPerThreadSubC + j)] =
p_a_block[a_block_mtx.Get1dIndex(k_begin + i,
m_repeat * MPerLevel1Cluster + j) +
mMyThreadOffsetA];
}
#else
static_assert(a_thread_sub_mtx.NCol() == 4, "asm only read 4xfp32");
#endif
}
}
// copy B-sub to form B
//#pragma unroll
for(index_t n_repeat = 0; n_repeat < NRepeat; ++n_repeat)
{
for(index_t i = 0; i < b_thread_sub_mtx.NRow(); ++i)
{
for(index_t j = 0; j < b_thread_sub_mtx.NCol(); ++j)
{
p_b_thread[b_thread_mtx.Get1dIndex(i, n_repeat * NPerThreadSubC + j)] =
p_b_block[b_block_mtx.Get1dIndex(k_begin + i,
n_repeat * MPerLevel1Cluster + j) +
mMyThreadOffsetB];
}
}
}
// loop over batch
//#pragma unroll
for(index_t ib = 0; ib + 1 < BatchPerThread; ++ib)
{
// do current batch of gemm
for(index_t k = 0; k < a_thread_mtx.NRow(); ++k)
{
#if 0
for(index_t i = 0; i < c_thread_mtx.NRow(); ++i)
{
for(index_t j = 0; j < c_thread_mtx.NCol(); ++j)
{
const index_t aindex =
a_thread_mtx.Get1dIndex(k, i); // A is transposed
const index_t bindex = b_thread_mtx.Get1dIndex(k, j);
const index_t cindex =
c_thread_mtx.Get1dIndex(i, j) + ib * ThreadMatrixStrideC;
f_accum(p_c_thread[cindex], p_a_thread[aindex] * p_b_thread[bindex]);
}
}
#elif 1
static_assert(c_thread_mtx.NRow() == 16 && c_thread_mtx.NCol() == 4,
"asm is only for 16x4");
const index_t bindex = b_thread_mtx.Get1dIndex(k, 0);
for(index_t i = 0; i < c_thread_mtx.NRow(); ++i)
{
const index_t aindex = a_thread_mtx.Get1dIndex(k, i); // A is transposed
const index_t cindex = c_thread_mtx.Get1dIndex(i, 0);
asm volatile("\n \
v_mac_f32 %0, %4, %5 \n \
v_mac_f32 %1, %4, %6 \n \
v_mac_f32 %2, %4, %7 \n \
v_mac_f32 %3, %4, %8 \n \
"
: "=v"(p_c_thread[cindex + 0]),
"=v"(p_c_thread[cindex + 1]),
"=v"(p_c_thread[cindex + 2]),
"=v"(p_c_thread[cindex + 3])
: "v"(p_a_thread[aindex]),
"v"(p_b_thread[bindex + 0]),
"v"(p_b_thread[bindex + 1]),
"v"(p_b_thread[bindex + 2]),
"v"(p_b_thread[bindex + 3]),
"0"(p_c_thread[cindex + 0]),
"1"(p_c_thread[cindex + 1]),
"2"(p_c_thread[cindex + 2]),
"3"(p_c_thread[cindex + 3]));
}
#endif
}
// read next batch of a, b
if(BlockMatrixStrideA != 0)
{
//#pragma unroll
for(index_t m_repeat = 0; m_repeat < MRepeat; ++m_repeat)
{
for(index_t i = 0; i < a_thread_sub_mtx.NRow(); ++i)
{
for(index_t j = 0; j < a_thread_sub_mtx.NCol(); ++j)
{
p_a_thread[a_thread_mtx.Get1dIndex(i,
m_repeat * MPerThreadSubC + j)] =
p_a_block[a_block_mtx.Get1dIndex(
k_begin + i, m_repeat * MPerLevel1Cluster + j) +
(ib + 1) * BlockMatrixStrideA + mMyThreadOffsetA];
}
}
}
}
if(BlockMatrixStrideB != 0)
{
//#pragma unroll
for(index_t n_repeat = 0; n_repeat < NRepeat; ++n_repeat)
{
for(index_t i = 0; i < b_thread_sub_mtx.NRow(); ++i)
{
for(index_t j = 0; j < b_thread_sub_mtx.NCol(); ++j)
{
p_b_thread[b_thread_mtx.Get1dIndex(i,
n_repeat * NPerThreadSubC + j)] =
p_b_block[b_block_mtx.Get1dIndex(
k_begin + i, n_repeat * MPerLevel1Cluster + j) +
(ib + 1) * BlockMatrixStrideB + mMyThreadOffsetB];
}
}
}
}
}
// do last batch of gemm
for(index_t k = 0; k < a_thread_mtx.NRow(); ++k)
{
#if 0
for(index_t i = 0; i < c_thread_mtx.NRow(); ++i)
{
for(index_t j = 0; j < c_thread_mtx.NCol(); ++j)
{
const index_t aindex = a_thread_mtx.Get1dIndex(k, i); // A is transposed
const index_t bindex = b_thread_mtx.Get1dIndex(k, j);
const index_t cindex = c_thread_mtx.Get1dIndex(i, j) +
(BatchPerThread - 1) * ThreadMatrixStrideC;
f_accum(p_c_thread[cindex], p_a_thread[aindex] * p_b_thread[bindex]);
}
}
#elif 1
static_assert(c_thread_mtx.NRow() == 16 && c_thread_mtx.NCol() == 4,
"asm is only for 16x4");
const index_t bindex = b_thread_mtx.Get1dIndex(k, 0);
for(index_t i = 0; i < c_thread_mtx.NRow(); ++i)
{
const index_t aindex = a_thread_mtx.Get1dIndex(k, i); // A is transposed
const index_t cindex =
c_thread_mtx.Get1dIndex(i, 0) + (BatchPerThread - 1) * ThreadMatrixStrideC;
asm volatile("\n \
v_mac_f32 %0, %4, %5 \n \
v_mac_f32 %1, %4, %6 \n \
v_mac_f32 %2, %4, %7 \n \
v_mac_f32 %3, %4, %8 \n \
"
: "=v"(p_c_thread[cindex + 0]),
"=v"(p_c_thread[cindex + 1]),
"=v"(p_c_thread[cindex + 2]),
"=v"(p_c_thread[cindex + 3])
: "v"(p_a_thread[aindex]),
"v"(p_b_thread[bindex + 0]),
"v"(p_b_thread[bindex + 1]),
"v"(p_b_thread[bindex + 2]),
"v"(p_b_thread[bindex + 3]),
"0"(p_c_thread[cindex + 0]),
"1"(p_c_thread[cindex + 1]),
"2"(p_c_thread[cindex + 2]),
"3"(p_c_thread[cindex + 3]));
}
#endif
}
}
}
template <class BlockMatrixC, index_t BlockMatrixStrideC, class FloatC> template <class BlockMatrixC, index_t BlockMatrixStrideC, class FloatC>
__device__ void CopyThreadMatrixCToBlockMatrixC(const FloatC* __restrict__ p_c_thread, __device__ void CopyThreadMatrixCToBlockMatrixC(const FloatC* __restrict__ p_c_thread,
FloatC* __restrict__ p_c_block) const FloatC* __restrict__ p_c_block) const
......
src/include/blockwise_gemm.hip.hpp
View file @ bdbc0eaa
...@@ -3,215 +3,6 @@ ...@@ -3,215 +3,6 @@
extern "C" __attribute__((address_space(3))) void* __to_local(void* p)[[hc]]; extern "C" __attribute__((address_space(3))) void* __to_local(void* p)[[hc]];
template <index_t BlockSize,
class BlockMatrixA,
class BlockMatrixB,
class ThreadMatrixC,
bool TransA,
bool TransB,
bool TransC,
index_t KPerThreadLoop,
index_t MThreadPerCluster,
index_t NThreadPerCluster,
bool DistributeThreadAlongColumnFirst>
struct BlockwiseGemmBlockABlockBThreadC
{
index_t mMyThreadOffsetA = 0;
index_t mMyThreadOffsetB = 0;
struct MatrixIndex
{
index_t row;
index_t col;
};
__device__ BlockwiseGemmBlockABlockBThreadC()
{
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
const auto c_thread_mtx_index = GetBeginOfThreadMatrixC(get_thread_local_1d_id());
mMyThreadOffsetA = (!TransA) ? a_block_mtx.Get1dIndex(c_thread_mtx_index.row, 0)
: a_block_mtx.Get1dIndex(0, c_thread_mtx_index.row);
mMyThreadOffsetB = (!TransB) ? b_block_mtx.Get1dIndex(0, c_thread_mtx_index.col)
: b_block_mtx.Get1dIndex(c_thread_mtx_index.col, 0);
#if 0
if(get_thread_local_1d_id() == 0 && get_block_1d_id() == 0)
{
print_ConstantMatrixDescriptor(BlockMatrixA{}, "a_block_mtx: ");
print_ConstantMatrixDescriptor(BlockMatrixB{}, "b_block_mtx: ");
print_ConstantMatrixDescriptor(ThreadMatrixC{}, "c_thread_mtx: ");
printf("%u %u, %u %u %u, %u %u\n",
get_block_1d_id(),
get_thread_local_1d_id(),
c_thread_mtx_index.batch,
c_thread_mtx_index.row,
c_thread_mtx_index.col,
mMyThreadOffsetA,
mMyThreadOffsetB);
}
#endif
}
__device__ MatrixIndex GetBeginOfThreadMatrixC(index_t thread_id) const
{
if(TransA && (!TransB) && (!TransC))
{
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
static_assert(a_block_mtx.NRow() == b_block_mtx.NRow(),
"wrong! k dimension not consistent!");
constexpr index_t MPerBlock = a_block_mtx.NCol();
constexpr index_t NPerBlock = b_block_mtx.NCol();
constexpr auto c_thread_mtx = ThreadMatrixC{};
// divide thread work
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
static_assert(MPerBlock % (MPerThread * MThreadPerCluster) == 0,
"MPerBlock % (MPerThread * MThreadPerCluster) != 0");
static_assert(NPerBlock % (NPerThread * NThreadPerCluster) == 0,
"NPerBlock % (NPerThread * NThreadPerCluster) != 0");
constexpr index_t MClusterWork =
(MPerBlock + MPerThread * MThreadPerCluster - 1) / (MPerThread * MThreadPerCluster);
constexpr index_t NClusterWork =
(NPerBlock + NPerThread * NThreadPerCluster - 1) / (NPerThread * NThreadPerCluster);
static_assert(BlockSize ==
(MClusterWork * MThreadPerCluster) *
(NClusterWork * NThreadPerCluster),
"wrong! wrong BlockSize");
if(DistributeThreadAlongColumnFirst)
{
const index_t cluster_work_block_id =
thread_id / (MThreadPerCluster * NThreadPerCluster);
const index_t thread_work_cluster_id =
thread_id - cluster_work_block_id * (MThreadPerCluster * NThreadPerCluster);
const index_t m_cluster_work_block_id = cluster_work_block_id / NClusterWork;
const index_t n_cluster_work_block_id =
cluster_work_block_id - m_cluster_work_block_id * NClusterWork;
const index_t m_thread_work_cluster_id = thread_work_cluster_id / NThreadPerCluster;
const index_t n_thread_work_cluster_id =
thread_work_cluster_id - m_thread_work_cluster_id * NThreadPerCluster;
#if 0
if(get_block_1d_id() == 0)
{
printf("%u %u, \t"
"MClusterWork %u MThreadPerCluster %u NClusterWork %u NThreadPerCluster %u \t"
"m_cluster_work_block_id %u n_cluster_work_block_id %u \t"
"m_thread_work_cluster_id %u n_thread_work_cluster_id %u \t"
"\n",
get_block_1d_id(), get_thread_local_1d_id(),
MClusterWork, MThreadPerCluster, NClusterWork, NThreadPerCluster,
m_cluster_work_block_id, n_cluster_work_block_id,
m_thread_work_cluster_id, n_thread_work_cluster_id);
}
#endif
return MatrixIndex{m_cluster_work_block_id * (MThreadPerCluster * MPerThread) +
m_thread_work_cluster_id * MPerThread,
n_cluster_work_block_id * (NThreadPerCluster * NPerThread) +
n_thread_work_cluster_id * NPerThread};
}
else
{
// not implemented
assert(false);
}
}
else
{
// not implemented
assert(false);
}
}
// this should be optimized away if input is known
__device__ static MatrixIndex GetDistanceFromBeginOfThreadMatrixC(index_t m_in_c,
index_t n_in_c)
{
return MatrixIndex{m_in_c, n_in_c};
}
template <class FloatA, class FloatB, class FloatC, class Accumulator>
__device__ void Run(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread,
Accumulator f_accum) const
{
if(TransA && (!TransB) && (!TransC))
{
constexpr auto True = integral_constant<bool, true>{};
constexpr auto False = integral_constant<bool, false>{};
constexpr auto a_block_mtx = BlockMatrixA{};
constexpr auto b_block_mtx = BlockMatrixB{};
constexpr auto c_thread_mtx = ThreadMatrixC{};
constexpr index_t KPerBlock = a_block_mtx.NRow(); // A is transposed
constexpr index_t MPerThread = c_thread_mtx.NRow();
constexpr index_t NPerThread = c_thread_mtx.NCol();
// a is transposed, b is not
constexpr auto a_thread_mtx =
make_ConstantMatrixDescriptor(Number<KPerThreadLoop>{}, Number<MPerThread>{});
constexpr auto b_thread_mtx =
make_ConstantMatrixDescriptor(Number<KPerThreadLoop>{}, Number<NPerThread>{});
FloatA p_a_thread[a_thread_mtx.GetElementSpace()];
FloatB p_b_thread[b_thread_mtx.GetElementSpace()];
// loop over k
for(index_t k_begin = 0; k_begin < KPerBlock; k_begin += KPerThreadLoop)
{
threadwise_matrix_copy(a_block_mtx,
p_a_block + mMyThreadOffsetA +
k_begin * a_block_mtx.RowStride(),
a_thread_mtx,
p_a_thread,
a_thread_mtx.GetLengths());
threadwise_matrix_copy(b_block_mtx,
p_b_block + mMyThreadOffsetB +
k_begin * b_block_mtx.RowStride(),
b_thread_mtx,
p_b_thread,
b_thread_mtx.GetLengths());
threadwise_gemm(a_thread_mtx,
True,
p_a_thread,
b_thread_mtx,
False,
p_b_thread,
c_thread_mtx,
False,
p_c_thread,
f_accum);
}
}
}
};
// if following number are power of 2, index calculation shall be greatly reduced: // if following number are power of 2, index calculation shall be greatly reduced:
// MPerThreadSubC, NPerThreadSubC, MLevel0Cluster, NLevel0Cluster, MLevel1Cluster, NLevel1Cluster // MPerThreadSubC, NPerThreadSubC, MLevel0Cluster, NLevel0Cluster, MLevel1Cluster, NLevel1Cluster
template <index_t BlockSize, template <index_t BlockSize,
...@@ -1149,10 +940,10 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2 ...@@ -1149,10 +940,10 @@ struct BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2
} }
template <class FloatA, class FloatB, class FloatC, class Accumulator> template <class FloatA, class FloatB, class FloatC, class Accumulator>
__device__ void Run_v2(const FloatA* __restrict__ p_a_block, __device__ void Run_PipelineReadAndCompute(const FloatA* __restrict__ p_a_block,
const FloatB* __restrict__ p_b_block, const FloatB* __restrict__ p_b_block,
FloatC* __restrict__ p_c_thread, FloatC* __restrict__ p_c_thread,
Accumulator f_accum) const Accumulator f_accum) const
{ {
constexpr auto True = integral_constant<bool, true>{}; constexpr auto True = integral_constant<bool, true>{};
constexpr auto False = integral_constant<bool, false>{}; constexpr auto False = integral_constant<bool, false>{};
......
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