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xgboost/cub/test/test_device_scan.cu view on Meta::CPAN
/******************************************************************************
* Copyright (c) 2011, Duane Merrill. All rights reserved.
* Copyright (c) 2011-2016, NVIDIA CORPORATION. All rights reserved.
*
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* modification, are permitted provided that the following conditions are met:
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* notice, this list of conditions and the following disclaimer.
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* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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******************************************************************************/
/******************************************************************************
* Test of DeviceScan utilities
******************************************************************************/
// Ensure printing of CUDA runtime errors to console
#define CUB_STDERR
#include <stdio.h>
#include <typeinfo>
#include <cub/util_allocator.cuh>
#include <cub/iterator/constant_input_iterator.cuh>
#include <cub/iterator/discard_output_iterator.cuh>
#include <cub/device/device_scan.cuh>
#include <thrust/device_ptr.h>
#include <thrust/scan.h>
#include "test_util.h"
using namespace cub;
//---------------------------------------------------------------------
// Globals, constants and typedefs
//---------------------------------------------------------------------
bool g_verbose = false;
int g_timing_iterations = 0;
int g_repeat = 0;
double g_device_giga_bandwidth;
CachingDeviceAllocator g_allocator(true);
// Dispatch types
enum Backend
{
CUB, // CUB method
THRUST, // Thrust method
CDP, // GPU-based (dynamic parallelism) dispatch to CUB method
};
/**
* \brief WrapperFunctor (for precluding test-specialized dispatch to *Sum variants)
*/
template<typename OpT>
struct WrapperFunctor
{
OpT op;
WrapperFunctor(OpT op) : op(op) {}
template <typename T>
__host__ __device__ __forceinline__ T operator()(const T &a, const T &b) const
{
return op(a, b);
}
};
//---------------------------------------------------------------------
// Dispatch to different CUB DeviceScan entrypoints
//---------------------------------------------------------------------
/**
* Dispatch to exclusive scan entrypoint
*/
template <typename IsPrimitiveT, typename InputIteratorT, typename OutputIteratorT, typename ScanOpT, typename InitialValueT, typename OffsetT>
CUB_RUNTIME_FUNCTION __forceinline__
cudaError_t Dispatch(
Int2Type<CUB> dispatch_to,
IsPrimitiveT is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
InitialValueT initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
cudaError_t error = cudaSuccess;
for (int i = 0; i < timing_timing_iterations; ++i)
{
error = DeviceScan::ExclusiveScan(d_temp_storage, temp_storage_bytes, d_in, d_out, scan_op, initial_value, num_items, stream, debug_synchronous);
}
return error;
}
/**
* Dispatch to exclusive sum entrypoint
*/
template <typename InputIteratorT, typename OutputIteratorT, typename InitialValueT, typename OffsetT>
CUB_RUNTIME_FUNCTION __forceinline__
cudaError_t Dispatch(
Int2Type<CUB> dispatch_to,
Int2Type<true> is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
Sum scan_op,
InitialValueT initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
cudaError_t error = cudaSuccess;
for (int i = 0; i < timing_timing_iterations; ++i)
{
error = DeviceScan::ExclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items, stream, debug_synchronous);
}
return error;
}
/**
* Dispatch to inclusive scan entrypoint
*/
template <typename IsPrimitiveT, typename InputIteratorT, typename OutputIteratorT, typename ScanOpT, typename OffsetT>
CUB_RUNTIME_FUNCTION __forceinline__
cudaError_t Dispatch(
Int2Type<CUB> dispatch_to,
IsPrimitiveT is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
NullType initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
cudaError_t error = cudaSuccess;
for (int i = 0; i < timing_timing_iterations; ++i)
{
error = DeviceScan::InclusiveScan(d_temp_storage, temp_storage_bytes, d_in, d_out, scan_op, num_items, stream, debug_synchronous);
}
return error;
}
/**
* Dispatch to inclusive sum entrypoint
*/
template <typename InputIteratorT, typename OutputIteratorT, typename OffsetT>
CUB_RUNTIME_FUNCTION __forceinline__
cudaError_t Dispatch(
Int2Type<CUB> dispatch_to,
Int2Type<true> is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
Sum scan_op,
NullType initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
cudaError_t error = cudaSuccess;
for (int i = 0; i < timing_timing_iterations; ++i)
{
error = DeviceScan::InclusiveSum(d_temp_storage, temp_storage_bytes, d_in, d_out, num_items, stream, debug_synchronous);
}
return error;
}
//---------------------------------------------------------------------
// Dispatch to different Thrust entrypoints
//---------------------------------------------------------------------
/**
* Dispatch to exclusive scan entrypoint
*/
template <typename IsPrimitiveT, typename InputIteratorT, typename OutputIteratorT, typename ScanOpT, typename InitialValueT, typename OffsetT>
cudaError_t Dispatch(
Int2Type<THRUST> dispatch_to,
IsPrimitiveT is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
InitialValueT initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
// The input value type
typedef typename std::iterator_traits<InputIteratorT>::value_type InputT;
// The output value type
typedef typename If<(Equals<typename std::iterator_traits<OutputIteratorT>::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ?
typename std::iterator_traits<InputIteratorT>::value_type, // ... then the input iterator's value type,
typename std::iterator_traits<OutputIteratorT>::value_type>::Type OutputT; // ... else the output iterator's value type
if (d_temp_storage == 0)
{
temp_storage_bytes = 1;
}
else
{
thrust::device_ptr<InputT> d_in_wrapper(d_in);
thrust::device_ptr<OutputT> d_out_wrapper(d_out);
for (int i = 0; i < timing_timing_iterations; ++i)
{
thrust::exclusive_scan(d_in_wrapper, d_in_wrapper + num_items, d_out_wrapper, initial_value, scan_op);
}
}
return cudaSuccess;
}
/**
* Dispatch to exclusive sum entrypoint
*/
template <typename InputIteratorT, typename OutputIteratorT, typename InitialValueT, typename OffsetT>
cudaError_t Dispatch(
Int2Type<THRUST> dispatch_to,
Int2Type<true> is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
Sum scan_op,
InitialValueT initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
// The input value type
typedef typename std::iterator_traits<InputIteratorT>::value_type InputT;
// The output value type
typedef typename If<(Equals<typename std::iterator_traits<OutputIteratorT>::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ?
typename std::iterator_traits<InputIteratorT>::value_type, // ... then the input iterator's value type,
typename std::iterator_traits<OutputIteratorT>::value_type>::Type OutputT; // ... else the output iterator's value type
if (d_temp_storage == 0)
{
temp_storage_bytes = 1;
}
else
{
thrust::device_ptr<InputT> d_in_wrapper(d_in);
thrust::device_ptr<OutputT> d_out_wrapper(d_out);
for (int i = 0; i < timing_timing_iterations; ++i)
{
thrust::exclusive_scan(d_in_wrapper, d_in_wrapper + num_items, d_out_wrapper);
}
}
return cudaSuccess;
}
/**
* Dispatch to inclusive scan entrypoint
*/
template <typename IsPrimitiveT, typename InputIteratorT, typename OutputIteratorT, typename ScanOpT, typename OffsetT>
cudaError_t Dispatch(
Int2Type<THRUST> dispatch_to,
IsPrimitiveT is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
NullType initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
// The input value type
typedef typename std::iterator_traits<InputIteratorT>::value_type InputT;
// The output value type
typedef typename If<(Equals<typename std::iterator_traits<OutputIteratorT>::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ?
typename std::iterator_traits<InputIteratorT>::value_type, // ... then the input iterator's value type,
typename std::iterator_traits<OutputIteratorT>::value_type>::Type OutputT; // ... else the output iterator's value type
if (d_temp_storage == 0)
{
temp_storage_bytes = 1;
}
else
{
thrust::device_ptr<InputT> d_in_wrapper(d_in);
thrust::device_ptr<OutputT> d_out_wrapper(d_out);
for (int i = 0; i < timing_timing_iterations; ++i)
{
thrust::inclusive_scan(d_in_wrapper, d_in_wrapper + num_items, d_out_wrapper, scan_op);
}
}
return cudaSuccess;
}
/**
* Dispatch to inclusive sum entrypoint
*/
template <typename InputIteratorT, typename OutputIteratorT, typename OffsetT>
cudaError_t Dispatch(
Int2Type<THRUST> dispatch_to,
Int2Type<true> is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
Sum scan_op,
NullType initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
// The input value type
typedef typename std::iterator_traits<InputIteratorT>::value_type InputT;
// The output value type
typedef typename If<(Equals<typename std::iterator_traits<OutputIteratorT>::value_type, void>::VALUE), // OutputT = (if output iterator's value type is void) ?
typename std::iterator_traits<InputIteratorT>::value_type, // ... then the input iterator's value type,
typename std::iterator_traits<OutputIteratorT>::value_type>::Type OutputT; // ... else the output iterator's value type
if (d_temp_storage == 0)
{
temp_storage_bytes = 1;
}
else
{
thrust::device_ptr<InputT> d_in_wrapper(d_in);
thrust::device_ptr<OutputT> d_out_wrapper(d_out);
for (int i = 0; i < timing_timing_iterations; ++i)
{
thrust::inclusive_scan(d_in_wrapper, d_in_wrapper + num_items, d_out_wrapper);
}
}
return cudaSuccess;
}
//---------------------------------------------------------------------
// CUDA Nested Parallelism Test Kernel
//---------------------------------------------------------------------
/**
* Simple wrapper kernel to invoke DeviceScan
*/
template <typename IsPrimitiveT, typename InputIteratorT, typename OutputIteratorT, typename ScanOpT, typename InitialValueT, typename OffsetT>
__global__ void CnpDispatchKernel(
IsPrimitiveT is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
InitialValueT initial_value,
OffsetT num_items,
bool debug_synchronous)
{
#ifndef CUB_CDP
*d_cdp_error = cudaErrorNotSupported;
#else
*d_cdp_error = Dispatch(
Int2Type<CUB>(),
is_primitive,
timing_timing_iterations,
d_temp_storage_bytes,
d_cdp_error,
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
initial_value,
num_items,
0,
debug_synchronous);
*d_temp_storage_bytes = temp_storage_bytes;
#endif
}
/**
* Dispatch to CDP kernel
*/
template <typename IsPrimitiveT, typename InputIteratorT, typename OutputIteratorT, typename ScanOpT, typename InitialValueT, typename OffsetT>
cudaError_t Dispatch(
Int2Type<CDP> dispatch_to,
IsPrimitiveT is_primitive,
int timing_timing_iterations,
size_t *d_temp_storage_bytes,
cudaError_t *d_cdp_error,
void* d_temp_storage,
size_t& temp_storage_bytes,
InputIteratorT d_in,
OutputIteratorT d_out,
ScanOpT scan_op,
InitialValueT initial_value,
OffsetT num_items,
cudaStream_t stream,
bool debug_synchronous)
{
// Invoke kernel to invoke device-side dispatch
CnpDispatchKernel<<<1,1>>>(
is_primitive,
timing_timing_iterations,
d_temp_storage_bytes,
d_cdp_error,
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
initial_value,
num_items,
debug_synchronous);
// Copy out temp_storage_bytes
CubDebugExit(cudaMemcpy(&temp_storage_bytes, d_temp_storage_bytes, sizeof(size_t) * 1, cudaMemcpyDeviceToHost));
// Copy out error
cudaError_t retval;
CubDebugExit(cudaMemcpy(&retval, d_cdp_error, sizeof(cudaError_t) * 1, cudaMemcpyDeviceToHost));
return retval;
}
//---------------------------------------------------------------------
// Test generation
//---------------------------------------------------------------------
/**
* Initialize problem
*/
template <typename T>
void Initialize(
GenMode gen_mode,
T *h_in,
int num_items)
{
for (int i = 0; i < num_items; ++i)
{
InitValue(gen_mode, h_in[i], i);
}
if (g_verbose)
{
printf("Input:\n");
DisplayResults(h_in, num_items);
printf("\n\n");
}
}
/**
* Solve exclusive-scan problem
*/
template <
typename InputIteratorT,
typename OutputT,
typename ScanOpT>
void Solve(
InputIteratorT h_in,
OutputT *h_reference,
int num_items,
ScanOpT scan_op,
xgboost/cub/test/test_device_scan.cu view on Meta::CPAN
// Allocate CDP device arrays
size_t *d_temp_storage_bytes = NULL;
cudaError_t *d_cdp_error = NULL;
CubDebugExit(g_allocator.DeviceAllocate((void**)&d_temp_storage_bytes, sizeof(size_t) * 1));
CubDebugExit(g_allocator.DeviceAllocate((void**)&d_cdp_error, sizeof(cudaError_t) * 1));
// Allocate temporary storage
void *d_temp_storage = NULL;
size_t temp_storage_bytes = 0;
CubDebugExit(Dispatch(
Int2Type<BACKEND>(),
Int2Type<Traits<OutputT>::PRIMITIVE>(),
1,
d_temp_storage_bytes,
d_cdp_error,
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
initial_value,
num_items,
0,
true));
CubDebugExit(g_allocator.DeviceAllocate(&d_temp_storage, temp_storage_bytes));
// Clear device output array
CubDebugExit(cudaMemset(d_out, 0, sizeof(OutputT) * num_items));
// Run warmup/correctness iteration
CubDebugExit(Dispatch(
Int2Type<BACKEND>(),
Int2Type<Traits<OutputT>::PRIMITIVE>(),
1,
d_temp_storage_bytes,
d_cdp_error,
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
initial_value,
num_items,
0,
true));
// Check for correctness (and display results, if specified)
int compare = CompareDeviceResults(h_reference, d_out, num_items, true, g_verbose);
printf("\t%s", compare ? "FAIL" : "PASS");
// Flush any stdout/stderr
fflush(stdout);
fflush(stderr);
// Performance
GpuTimer gpu_timer;
gpu_timer.Start();
CubDebugExit(Dispatch(Int2Type<BACKEND>(),
Int2Type<Traits<OutputT>::PRIMITIVE>(),
g_timing_iterations,
d_temp_storage_bytes,
d_cdp_error,
d_temp_storage,
temp_storage_bytes,
d_in,
d_out,
scan_op,
initial_value,
num_items,
0,
false));
gpu_timer.Stop();
float elapsed_millis = gpu_timer.ElapsedMillis();
// Display performance
if (g_timing_iterations > 0)
{
float avg_millis = elapsed_millis / g_timing_iterations;
float giga_rate = float(num_items) / avg_millis / 1000.0f / 1000.0f;
float giga_bandwidth = giga_rate * (sizeof(InputT) + sizeof(OutputT));
printf(", %.3f avg ms, %.3f billion items/s, %.3f logical GB/s, %.1f%% peak", avg_millis, giga_rate, giga_bandwidth, giga_bandwidth / g_device_giga_bandwidth * 100.0);
}
printf("\n\n");
// Cleanup
if (d_out) CubDebugExit(g_allocator.DeviceFree(d_out));
if (d_temp_storage_bytes) CubDebugExit(g_allocator.DeviceFree(d_temp_storage_bytes));
if (d_cdp_error) CubDebugExit(g_allocator.DeviceFree(d_cdp_error));
if (d_temp_storage) CubDebugExit(g_allocator.DeviceFree(d_temp_storage));
// Correctness asserts
AssertEquals(0, compare);
}
/**
* Test DeviceScan on pointer type
*/
template <
Backend BACKEND,
typename InputT,
typename OutputT,
typename ScanOpT,
typename InitialValueT>
void TestPointer(
int num_items,
GenMode gen_mode,
ScanOpT scan_op,
InitialValueT initial_value)
{
printf("\nPointer %s %s cub::DeviceScan::%s %d items, %s->%s (%d->%d bytes) , gen-mode %s\n",
(BACKEND == CDP) ? "CDP CUB" : (BACKEND == THRUST) ? "Thrust" : "CUB",
(Equals<InitialValueT, NullType>::VALUE) ? "Inclusive" : "Exclusive",
(Equals<ScanOpT, Sum>::VALUE) ? "Sum" : "Scan",
num_items,
typeid(InputT).name(), typeid(OutputT).name(), (int) sizeof(InputT), (int) sizeof(OutputT),
(gen_mode == RANDOM) ? "RANDOM" : (gen_mode == INTEGER_SEED) ? "SEQUENTIAL" : "HOMOGENOUS");
fflush(stdout);
// Allocate host arrays
InputT* h_in = new InputT[num_items];
OutputT* h_reference = new OutputT[num_items];
// Initialize problem and solution
Initialize(gen_mode, h_in, num_items);
Solve(h_in, h_reference, num_items, scan_op, initial_value);
// Allocate problem device arrays
InputT *d_in = NULL;
CubDebugExit(g_allocator.DeviceAllocate((void**)&d_in, sizeof(InputT) * num_items));
// Initialize device input
CubDebugExit(cudaMemcpy(d_in, h_in, sizeof(InputT) * num_items, cudaMemcpyHostToDevice));
// Run Test
Test<BACKEND>(d_in, h_reference, num_items, scan_op, initial_value);
xgboost/cub/test/test_device_scan.cu view on Meta::CPAN
// Inclusive (no initial value)
Test<InputT, OutputT>(num_items, cub::Sum(), NullType());
Test<InputT, OutputT>(num_items, cub::Max(), NullType());
}
/**
* Test different input sizes
*/
template <
typename InputT,
typename OutputT>
void TestSize(
int num_items,
OutputT identity,
OutputT initial_value)
{
if (num_items < 0)
{
TestOp<InputT>(0, identity, initial_value);
TestOp<InputT>(1, identity, initial_value);
TestOp<InputT>(100, identity, initial_value);
TestOp<InputT>(10000, identity, initial_value);
TestOp<InputT>(1000000, identity, initial_value);
// Randomly select problem size between 1:10,000,000
unsigned int max_int = (unsigned int) -1;
for (int i = 0; i < 10; ++i)
{
unsigned int num_items;
RandomBits(num_items);
num_items = (unsigned int) ((double(num_items) * double(10000000)) / double(max_int));
num_items = CUB_MAX(1, num_items);
TestOp<InputT>(num_items, identity, initial_value);
}
}
else
{
TestOp<InputT>(num_items, identity, initial_value);
}
}
//---------------------------------------------------------------------
// Main
//---------------------------------------------------------------------
/**
* Main
*/
int main(int argc, char** argv)
{
int num_items = -1;
// Initialize command line
CommandLineArgs args(argc, argv);
g_verbose = args.CheckCmdLineFlag("v");
args.GetCmdLineArgument("n", num_items);
args.GetCmdLineArgument("i", g_timing_iterations);
args.GetCmdLineArgument("repeat", g_repeat);
// Print usage
if (args.CheckCmdLineFlag("help"))
{
printf("%s "
"[--n=<input items> "
"[--i=<timing iterations> "
"[--device=<device-id>] "
"[--repeat=<repetitions of entire test suite>]"
"[--v] "
"[--cdp]"
"\n", argv[0]);
exit(0);
}
// Initialize device
CubDebugExit(args.DeviceInit());
g_device_giga_bandwidth = args.device_giga_bandwidth;
printf("\n");
#ifdef QUICKER_TEST
// Compile/run basic CUB test
if (num_items < 0) num_items = 32000000;
TestPointer<CUB, char, int>( num_items , UNIFORM, Sum(), (int) (0));
TestPointer<CUB, int, int>( num_items , UNIFORM, Sum(), (int) (0));
#elif defined(QUICK_TEST)
// Get device ordinal
int device_ordinal;
CubDebugExit(cudaGetDevice(&device_ordinal));
// Get device SM version
int sm_version;
CubDebugExit(SmVersion(sm_version, device_ordinal));
// Compile/run quick tests
if (num_items < 0) num_items = 32000000;
TestPointer<CUB, char, char>( num_items * ((sm_version <= 130) ? 1 : 4), UNIFORM, Sum(), char(0));
TestPointer<THRUST, char, char>( num_items * ((sm_version <= 130) ? 1 : 4), UNIFORM, Sum(), char(0));
printf("----------------------------\n");
TestPointer<CUB, short, short>( num_items * ((sm_version <= 130) ? 1 : 2), UNIFORM, Sum(), short(0));
TestPointer<THRUST, short, short>( num_items * ((sm_version <= 130) ? 1 : 2), UNIFORM, Sum(), short(0));
printf("----------------------------\n");
TestPointer<CUB, int, int>( num_items , UNIFORM, Sum(), (int) (0));
TestPointer<THRUST, int, int>( num_items , UNIFORM, Sum(), (int) (0));
printf("----------------------------\n");
TestPointer<CUB, long long, long long>( num_items / 2, UNIFORM, Sum(), (long long) (0));
TestPointer<THRUST, long long, long long>(num_items / 2, UNIFORM, Sum(), (long long) (0));
printf("----------------------------\n");
TestPointer<CUB, TestBar, TestBar>( num_items / 4, UNIFORM, Sum(), TestBar());
TestPointer<THRUST, TestBar, TestBar>( num_items / 4, UNIFORM, Sum(), TestBar());
#else
// Compile/run thorough tests
for (int i = 0; i <= g_repeat; ++i)
{
// Test different input+output data types
TestSize<unsigned char>(num_items, (int) 0, (int) 99);
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