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[Not-for-merge] Try to implement kernels along axis with one kernel for IndexAxis0 #668

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[Not-for-merge] Try to implement kernels along axis with one kernel for IndexAxis0 #668

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6082f93
using pattern trasform_scan to merge two kenerls into one
qindazhu Jan 29, 2021
4147985
delete benchmark code as they should not be merged
qindazhu Jan 29, 2021
c8d516e
delete useless header
qindazhu Jan 29, 2021
bbe1d9e
try to implement the loop on axis with one kernel for IndexAxis0
qindazhu Feb 19, 2021
14383d7
add comments for transform_lbs
qindazhu Feb 19, 2021
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56 changes: 56 additions & 0 deletions k2/csrc/benchmark/ragged_ops_benchmark.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -114,6 +114,60 @@ static void RegisterBenchmarkSegmentedExclusiveSum(DeviceType device_type) {
}
}

static BenchmarkStat BenchmarkIndexAxis0(int32_t dim, DeviceType device_type) {
ContextPtr context;
if (device_type == kCpu) {
context = GetCpuContext();
} else {
K2_CHECK_EQ(device_type, kCuda);
context = GetCudaContext();
}

int32_t num_iter = 20;
int32_t min_num_elems = dim * 10;
int32_t max_num_elems = dim * 20;

int32_t num_axes = 4;
RaggedShape shape =
RandomRaggedShape(true, num_axes, num_axes, min_num_elems, max_num_elems)
.To(context);
int32_t dim0 = shape.Dim0(), result_dim0 = RandInt(0, dim0);
if (dim0 == 0) result_dim0 = 0;
std::vector<int32_t> new2old_vec(result_dim0);
for (int i = 0; i < result_dim0; i++) new2old_vec[i] = RandInt(-1, dim0 - 1);
Array1<int32_t> new2old(context, new2old_vec);
int32_t num_elems = shape.NumElements();
Array1<int32_t> value_indexes;

BenchmarkStat stat;
stat.op_name = "IndexAxis0New_" + std::to_string(num_axes) + "_" +
std::to_string(shape.Dim0()) + "_" + std::to_string(num_elems);
stat.num_iter = num_iter;
stat.problem_size = dim;
stat.dtype_name = TraitsOf(DtypeOf<int32_t>::dtype).Name();
stat.device_type = device_type;

stat.eplased_per_iter =
BenchmarkOp(num_iter, context,
(RaggedShape(*)(RaggedShape &, const Array1<int32_t> &,
Array1<int32_t> *))(&IndexAxis0New),
shape, new2old, &value_indexes);
stat.eplased_per_iter *= 1e6; // from seconds to microseconds
return stat;
}

static void RegisterBenchmarkIndexAxis0(DeviceType device_type) {
std::vector<int32_t> problems_sizes = {50, 100, 200, 500, 1000,
10000, 50000, 100000, 200000};
for (auto s : problems_sizes) {
std::string name =
GenerateBenchmarkName<int32_t>("IndexAxis0", device_type);
RegisterBenchmark(name, [s, device_type]() -> BenchmarkStat {
return BenchmarkIndexAxis0(s, device_type);
});
}
}

static void RunRaggedOpsBenchmark() {
PrintEnvironmentInfo();

Expand All @@ -122,6 +176,8 @@ static void RunRaggedOpsBenchmark() {
RegisterBenchmarkSegmentedExclusiveSum<int32_t>(kCpu);
RegisterBenchmarkSegmentedExclusiveSum<int32_t>(kCuda);

RegisterBenchmarkIndexAxis0(kCuda);

// Users can set a regular expression via environment
// variable `K2_BENCHMARK_FILTER` such that only benchmarks
// with name matching the pattern are candidates to run.
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