mirror of
https://github.com/KhronosGroup/OpenCL-CTS.git
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New subgroups - full changes set (#1074)
* Extended subgroups - extended types types * Extended subgroups - non uniform vote tests * Extended subgroups - non uniform arithmetic tests * Extended subgroups - ballot tests * Extended subgroups - clustered reduce tests * Extended subgroups - shuffle tests * Extended subgroups - formating issues * Extended subgroups - review fixes * Extended subgroups - review fixes Fixed: removed additional brakes, kernel_sstr * Extended subgroups - fix macos build error * Extended subgroups - review fixes Fixed: mac os build error * Extended subgroups - data type verification example * Extended subgroups - error unification * Extended subgroups - fix header years * Extended subgroups - use is_half_nan * Extended subgroups - compare half as float * Review fixes mostly for ballot functions. - Modify kernels for better handling active/inactive workitems - Modify gen/chk functions for handling non uniform workgroup sizes - Introduce new variables naming convention - minor fixes * Extended subgroups - simplification data generation for ballot lsb/msb functions * Extended subgroups - minor fixes * Extended subgroups - move common code to function * Extended subgroups - formatting errors fix * Extended subgroups - fix build error * Extended subgroups - sub_group_elect more sophisticated Define mask which is 4bytes pattern where bit 1 means work item is active. If workitem in subgroup matches pattern then run sub_group_elect() * Extended subgroups - fix Ubuntu build error * Extended subgroups - voting function review fixes * adjust all function for using masks * remove calculate templates * merge code to one common template * check results only in active workitems * normalize values on host side * minor fixes * Extended subgroups - fix typos * Set of fixes and improvements after review * define WorkGroupParams to stop extended parameters list in function * better workitems mask handing (WorkGroupParams) * narrow values of data input generation to avoid overflows (arithmetic func) * implement work item masks for arithmetic functions * enable half type testing for reduction/scan/broadcast * minor fixes * Extended subgroups - fix Linux issues * Extended subgroups - fix sub_group_local_id data type * Extended subgroups - use vector instead of array. * Extended subgroups - change names to subgroup * Extended subgroups - uncomment code, fix build * Extended subgroups - build fix, use cl_half_from_float func * Extended subgroups - remove is_half_nan * Extended subgroups - do no use undef min/max * Extended subgroups - use parenthesis, fix formatting
This commit is contained in:
Grzegorz Wawiorko
committed by
GitHub
GitHub
parent
c5e4ca6c91
commit
71bef8563e
340
test_conformance/subgroups/test_subgroup_clustered_reduce.cpp
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340
test_conformance/subgroups/test_subgroup_clustered_reduce.cpp
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//
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// Copyright (c) 2021 The Khronos Group Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//
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#include "procs.h"
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#include "subhelpers.h"
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#include "subgroup_common_templates.h"
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#include "harness/typeWrappers.h"
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#define CLUSTER_SIZE 4
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#define CLUSTER_SIZE_STR "4"
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namespace {
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static const char *redadd_clustered_source =
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"__kernel void test_redadd_clustered(const __global Type *in, __global "
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"int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_add(in[gid], " CLUSTER_SIZE_STR ")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = sub_group_clustered_reduce_add(in[gid], " CLUSTER_SIZE_STR
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");\n"
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"}\n";
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static const char *redmax_clustered_source =
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"__kernel void test_redmax_clustered(const __global Type *in, __global "
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"int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_max(in[gid], " CLUSTER_SIZE_STR ")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = sub_group_clustered_reduce_max(in[gid], " CLUSTER_SIZE_STR
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");\n"
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"}\n";
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static const char *redmin_clustered_source =
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"__kernel void test_redmin_clustered(const __global Type *in, __global "
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"int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_min(in[gid], " CLUSTER_SIZE_STR ")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = sub_group_clustered_reduce_min(in[gid], " CLUSTER_SIZE_STR
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");\n"
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"}\n";
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static const char *redmul_clustered_source =
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"__kernel void test_redmul_clustered(const __global Type *in, __global "
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"int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_mul(in[gid], " CLUSTER_SIZE_STR ")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = sub_group_clustered_reduce_mul(in[gid], " CLUSTER_SIZE_STR
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");\n"
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"}\n";
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static const char *redand_clustered_source =
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"__kernel void test_redand_clustered(const __global Type *in, __global "
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"int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_and(in[gid], " CLUSTER_SIZE_STR ")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = sub_group_clustered_reduce_and(in[gid], " CLUSTER_SIZE_STR
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");\n"
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"}\n";
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static const char *redor_clustered_source =
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"__kernel void test_redor_clustered(const __global Type *in, __global int4 "
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"*xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_or(in[gid], " CLUSTER_SIZE_STR ")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = sub_group_clustered_reduce_or(in[gid], " CLUSTER_SIZE_STR
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");\n"
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"}\n";
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static const char *redxor_clustered_source =
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"__kernel void test_redxor_clustered(const __global Type *in, __global "
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"int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_xor(in[gid], " CLUSTER_SIZE_STR ")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = sub_group_clustered_reduce_xor(in[gid], " CLUSTER_SIZE_STR
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");\n"
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"}\n";
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static const char *redand_clustered_logical_source =
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"__kernel void test_redand_clustered_logical(const __global Type *in, "
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"__global int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_logical_and(in[gid], " CLUSTER_SIZE_STR
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")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = "
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"sub_group_clustered_reduce_logical_and(in[gid], " CLUSTER_SIZE_STR ");\n"
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"}\n";
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static const char *redor_clustered_logical_source =
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"__kernel void test_redor_clustered_logical(const __global Type *in, "
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"__global int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if (sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_logical_or(in[gid], " CLUSTER_SIZE_STR
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")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = "
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"sub_group_clustered_reduce_logical_or(in[gid], " CLUSTER_SIZE_STR ");\n"
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"}\n";
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static const char *redxor_clustered_logical_source =
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"__kernel void test_redxor_clustered_logical(const __global Type *in, "
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"__global int4 *xy, __global Type *out)\n"
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"{\n"
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" int gid = get_global_id(0);\n"
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" XY(xy,gid);\n"
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" xy[gid].w = 0;\n"
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" if ( sizeof(in[gid]) == "
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"sizeof(sub_group_clustered_reduce_logical_xor(in[gid], " CLUSTER_SIZE_STR
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")))\n"
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" {xy[gid].w = sizeof(in[gid]);}\n"
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" out[gid] = "
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"sub_group_clustered_reduce_logical_xor(in[gid], " CLUSTER_SIZE_STR ");\n"
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"}\n";
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// DESCRIPTION:
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// Test for reduce cluster functions
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template <typename Ty, ArithmeticOp operation> struct RED_CLU
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{
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static void gen(Ty *x, Ty *t, cl_int *m, const WorkGroupParams &test_params)
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{
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int nw = test_params.local_workgroup_size;
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int ns = test_params.subgroup_size;
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int ng = test_params.global_workgroup_size;
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ng = ng / nw;
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log_info(" sub_group_clustered_reduce_%s(%s, %d bytes) ...\n",
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operation_names(operation), TypeManager<Ty>::name(),
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sizeof(Ty));
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genrand<Ty, operation>(x, t, m, ns, nw, ng);
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}
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static int chk(Ty *x, Ty *y, Ty *mx, Ty *my, cl_int *m,
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const WorkGroupParams &test_params)
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{
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int nw = test_params.local_workgroup_size;
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int ns = test_params.subgroup_size;
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int ng = test_params.global_workgroup_size;
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int nj = (nw + ns - 1) / ns;
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ng = ng / nw;
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for (int k = 0; k < ng; ++k)
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{
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std::vector<cl_int> data_type_sizes;
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// Map to array indexed to array indexed by local ID and sub group
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for (int j = 0; j < nw; ++j)
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{
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mx[j] = x[j];
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my[j] = y[j];
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data_type_sizes.push_back(m[4 * j + 3]);
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}
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for (cl_int dts : data_type_sizes)
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{
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if (dts != sizeof(Ty))
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{
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log_error("ERROR: sub_group_clustered_reduce_%s(%s) "
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"wrong data type size detected, expected: %d, "
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"used by device %d, in group %d\n",
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operation_names(operation),
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TypeManager<Ty>::name(), sizeof(Ty), dts, k);
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return TEST_FAIL;
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}
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}
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for (int j = 0; j < nj; ++j)
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{
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int ii = j * ns;
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int n = ii + ns > nw ? nw - ii : ns;
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int midx = 4 * ii + 2;
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std::vector<Ty> clusters_results;
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int clusters_counter = ns / CLUSTER_SIZE;
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clusters_results.resize(clusters_counter);
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// Compute target
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Ty tr = mx[ii];
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for (int i = 0; i < n; ++i)
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{
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if (i % CLUSTER_SIZE == 0)
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tr = mx[ii + i];
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else
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tr = calculate<Ty>(tr, mx[ii + i], operation);
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clusters_results[i / CLUSTER_SIZE] = tr;
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}
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// Check result
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for (int i = 0; i < n; ++i)
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{
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Ty rr = my[ii + i];
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tr = clusters_results[i / CLUSTER_SIZE];
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if (!compare(rr, tr))
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{
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log_error(
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"ERROR: sub_group_clustered_reduce_%s(%s) mismatch "
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"for local id %d in sub group %d in group %d\n",
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operation_names(operation), TypeManager<Ty>::name(),
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i, j, k);
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return TEST_FAIL;
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}
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}
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}
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x += nw;
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y += nw;
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m += 4 * nw;
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}
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log_info(" sub_group_clustered_reduce_%s(%s, %d bytes) ... passed\n",
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operation_names(operation), TypeManager<Ty>::name(),
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sizeof(Ty));
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return TEST_PASS;
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}
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};
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template <typename T>
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int run_cluster_red_add_max_min_mul_for_type(RunTestForType rft)
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{
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int error = rft.run_impl<T, RED_CLU<T, ArithmeticOp::add_>>(
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"test_redadd_clustered", redadd_clustered_source);
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error |= rft.run_impl<T, RED_CLU<T, ArithmeticOp::max_>>(
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"test_redmax_clustered", redmax_clustered_source);
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error |= rft.run_impl<T, RED_CLU<T, ArithmeticOp::min_>>(
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"test_redmin_clustered", redmin_clustered_source);
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error |= rft.run_impl<T, RED_CLU<T, ArithmeticOp::mul_>>(
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"test_redmul_clustered", redmul_clustered_source);
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return error;
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}
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template <typename T> int run_cluster_and_or_xor_for_type(RunTestForType rft)
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{
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int error = rft.run_impl<T, RED_CLU<T, ArithmeticOp::and_>>(
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"test_redand_clustered", redand_clustered_source);
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error |= rft.run_impl<T, RED_CLU<T, ArithmeticOp::or_>>(
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"test_redor_clustered", redor_clustered_source);
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error |= rft.run_impl<T, RED_CLU<T, ArithmeticOp::xor_>>(
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"test_redxor_clustered", redxor_clustered_source);
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return error;
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}
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template <typename T>
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int run_cluster_logical_and_or_xor_for_type(RunTestForType rft)
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{
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int error = rft.run_impl<T, RED_CLU<T, ArithmeticOp::logical_and>>(
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"test_redand_clustered_logical", redand_clustered_logical_source);
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error |= rft.run_impl<T, RED_CLU<T, ArithmeticOp::logical_or>>(
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"test_redor_clustered_logical", redor_clustered_logical_source);
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error |= rft.run_impl<T, RED_CLU<T, ArithmeticOp::logical_xor>>(
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"test_redxor_clustered_logical", redxor_clustered_logical_source);
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return error;
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}
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}
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int test_subgroup_functions_clustered_reduce(cl_device_id device,
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cl_context context,
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cl_command_queue queue,
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int num_elements)
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{
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std::vector<std::string> required_extensions = {
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"cl_khr_subgroup_clustered_reduce"
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};
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constexpr size_t global_work_size = 2000;
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constexpr size_t local_work_size = 200;
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WorkGroupParams test_params(global_work_size, local_work_size,
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required_extensions);
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RunTestForType rft(device, context, queue, num_elements, test_params);
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int error = run_cluster_red_add_max_min_mul_for_type<cl_int>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_uint>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_long>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_ulong>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_short>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_ushort>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_char>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_uchar>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_float>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<cl_double>(rft);
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error |= run_cluster_red_add_max_min_mul_for_type<subgroups::cl_half>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_int>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_uint>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_long>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_ulong>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_short>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_ushort>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_char>(rft);
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error |= run_cluster_and_or_xor_for_type<cl_uchar>(rft);
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error |= run_cluster_logical_and_or_xor_for_type<cl_int>(rft);
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return error;
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}
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