Merge branch 'develop' into dyn_resize_gather

src/targets/gpu/device/targets.hpp.in

+/*
+* The MIT License (MIT)
+*
+* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
+*
+* Permission is hereby granted, free of charge, to any person obtaining a copy
+* of this software and associated documentation files (the "Software"), to deal
+* in the Software without restriction, including without limitation the rights
+* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+* copies of the Software, and to permit persons to whom the Software is
+* furnished to do so, subject to the following conditions:
+*
+* The above copyright notice and this permission notice shall be included in
+* all copies or substantial portions of the Software.
+*
+* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+* THE SOFTWARE.
+*/
+#ifndef MIGRAPHX_GUARD_DEVICE_TARGETS_CPP
+#define MIGRAPHX_GUARD_DEVICE_TARGETS_CPP
+
+#include <migraphx/gpu/device/config.hpp>
+#include <string>
+#include <vector>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+namespace device {
+#define MIGRAPHX_GPU_TARGETS "@GPU_TARGETS@" // NOLINT
+
+MIGRAPHX_DEVICE_EXPORT
+const std::vector<std::string>& get_targets();
+
+MIGRAPHX_DEVICE_EXPORT
+std::string get_targets_as_string();
+
+MIGRAPHX_DEVICE_EXPORT
+std::string get_device_name();
+
+} // namespace device
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+#endif // MIGRAPHX_GUARD_DEVICE_TARGETS_CPP
+
+

src/targets/gpu/driver/compile_op.cpp

@@ -38,10 +38,8 @@ struct compile_op : action<compile_op>
         context ctx;
         auto inputs = p.parse_shapes(v.at("inputs"));
         auto op     = gpu::compile_op(v.at("name").to<std::string>(), ctx, inputs, v);
-        auto [host_time, device_time] = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
-        std::cout << op << ": " << host_time << "ms";
-        if(device_time > 0)
-            std::cout << ", " << device_time << "ms";
+        auto t      = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
+        std::cout << op << ": " << t << "ms";
         std::cout << std::endl;
     }
 };

src/targets/gpu/driver/run_op.cpp

@@ -43,8 +43,8 @@ struct run_op : action<run_op>
         auto op = make_op(name);
         if(v.contains("fields"))
             op.from_value(v.at("fields"));
-        auto [host_time, device_time] = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
-        std::cout << op << ": " << host_time << "ms" << std::endl;
+        auto t = time_op(ctx, op, inputs, p.get(v, "iterations", 100));
+        std::cout << op << ": " << t << "ms" << std::endl;
     }
 };
 

src/targets/gpu/fuse_ck.cpp

@@ -22,10 +22,11 @@
  * THE SOFTWARE.
  */
 #include <migraphx/gpu/fuse_ck.hpp>
+#include <migraphx/gpu/gemm_softmax_gemm.hpp>
 #include <migraphx/matcher.hpp>
 #include <migraphx/pass_manager.hpp>
-#include <migraphx/make_op.hpp>
 #include <migraphx/register_op.hpp>
+#include <migraphx/gpu/device_name.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -55,7 +56,7 @@ struct ck_gemm
     {
         check_shapes{inputs, *this}.same_ndims();
         if(inputs.size() < 2)
-            MIGRAPHX_THROW("should have at least two inputs.");
+            MIGRAPHX_THROW(name() + ": should have at least two inputs.");
         auto a = inputs[0];
         auto b = inputs[1];
         for(const auto& input : inputs)
@@ -65,27 +66,35 @@ struct ck_gemm
             return r;
         return r.with_type(mods.front()->get_output_shapes().front().type());
     }
+
+    static bool is_ck_supported_type(shape::type_t t)
+    {
+        return contains({shape::half_type, shape::int8_type, shape::int32_type}, t);
+    }
 };
 MIGRAPHX_REGISTER_OP(ck_gemm);
 
-namespace {
-
-bool is_ck_supported_type(shape::type_t t)
+struct ck_gemm_softmax_gemm : gemm_softmax_gemm
 {
-    return contains({shape::half_type, shape::int8_type, shape::int32_type}, t);
-}
+    std::string name() const { return "gpu::ck_gemm_softmax_gemm"; }
+};
+MIGRAPHX_REGISTER_OP(ck_gemm_softmax_gemm);
+
+namespace {
 
 MIGRAPHX_PRED_MATCHER(is_ck_gemm, instruction_ref ins)
 {
     if(ins->name() != "dot" and ins->name() != "quant_dot")
         return false;
-    if(not is_ck_supported_type(ins->get_shape().type()))
+    if(not ck_gemm::is_ck_supported_type(ins->get_shape().type()))
         return false;
     auto a = ins->inputs().front()->get_shape();
     auto b = ins->inputs().back()->get_shape();
     auto m = a.lens()[a.lens().size() - 2];
     auto n = b.lens().back();
     auto k = a.lens().back();
+    auto batch_size = std::accumulate(
+        a.lens().rbegin() + 2, a.lens().rend(), std::size_t{1}, std::multiplies<std::size_t>());
     // Integer gemms must be divisible by 4 in ck
     if(contains({shape::int8_type, shape::int32_type}, ins->get_shape().type()))
     {
@@ -96,9 +105,17 @@ MIGRAPHX_PRED_MATCHER(is_ck_gemm, instruction_ref ins)
         if(k % 4 != 0)
             return false;
     }
-    // Skipping GEMMs with a K dimension greater than 2048 is a course-grained strategy
-    // to avoid poor-performing GEMM kernels from CK
-    // To-do: Investigate a more precise strategy
+    auto device_name = trim(split_string(get_device_name(), ':').front());
+    if(device_name == "gfx940")
+    {
+        if(ins->get_shape().type() == shape::half_type)
+        {
+            if(batch_size >= 64)
+                return m < 2048 or k <= 64 or n <= 384 or n >= 2048;
+            return true;
+        }
+        return true;
+    }
     return k <= 2048;
 }
 
@@ -127,7 +144,15 @@ struct find_ck_gemm_pointwise
            ins->get_shape().type() != gemm_ins->get_shape().type())
             return;
         if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [](auto input) {
-               return not is_ck_supported_type(input->get_shape().type());
+               return not ck_gemm::is_ck_supported_type(input->get_shape().type());
+           }))
+            return;
+        if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [](auto input) {
+               return not input->inputs().empty() and input->inputs().front()->name() == "capture";
+           }))
+            return;
+        if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [](auto input) {
+               return not input->inputs().empty() and input->inputs().front()->name() == "capture";
            }))
             return;
         assert(gemm_it != inputs.end());
@@ -152,7 +177,7 @@ struct find_ck_gemm_pointwise
 
 struct find_ck_gemm
 {
-    auto matcher() const { return match::name("dot")(is_ck_gemm().bind("gemm")); }
+    auto matcher() const { return match::name("dot", "quant_dot")(is_ck_gemm().bind("gemm")); }
 
     void apply(module_pass_manager& mpm, const match::matcher_result& r) const
     {
@@ -161,11 +186,26 @@ struct find_ck_gemm
     }
 };
 
+struct find_ck_gemm_softmax_gemm
+{
+    auto matcher() const { return match::name("gpu::pre_gemm_softmax_gemm"); }
+
+    void apply(module_pass_manager& mpm, const match::matcher_result& r) const
+    {
+        auto ins = r.result;
+        auto v   = ins->get_operator().to_value();
+        assert(v.contains("scale"));
+        auto scale = v.at("scale").to<float>();
+        mpm.get_module().replace_instruction(
+            ins, ck_gemm_softmax_gemm{migraphx::make_op("dot"), scale}, ins->inputs());
+    }
+};
+
 } // namespace
 
 void fuse_ck::apply(module_pass_manager& mpm) const
 {
-    match::find_matches(mpm, find_ck_gemm_pointwise{});
+    match::find_matches(mpm, find_ck_gemm_softmax_gemm{}, find_ck_gemm_pointwise{});
     match::find_matches(mpm, find_ck_gemm{});
 }
 

src/targets/gpu/fuse_mlir.cpp

@@ -36,24 +36,14 @@ struct module;
 
 namespace gpu {
 
-MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_MLIR);
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_EXTRA_MLIR);
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_DISABLE_MLIR);
 
 bool mlir_enabled()
 {
 #ifdef MIGRAPHX_MLIR
-    const bool mlir_enabled = enabled(MIGRAPHX_ENABLE_MLIR{});
-    if(mlir_enabled)
-    {
-        return true;
-    }
-    else
-    {
-
-        std::cerr << "WARNING: MIGraphX built with MLIR but it is not enabled. Please set the env "
-                     "var MIGRAPHX_ENABLE_MLIR to use MLIR kernel generator."
-                  << std::endl;
-        return false;
-    }
+    const bool mlir_disabled = enabled(MIGRAPHX_DISABLE_MLIR{});
+    return not mlir_disabled;
 #else
     return false;
 #endif
@@ -103,7 +93,10 @@ struct mlir_op
             }
             if(ins->name() == "@return")
             {
-                return ins_shapes[ins->inputs().at(0)].with_type(type);
+                auto s = ins_shapes[ins->inputs().at(0)].with_type(type);
+                if(not s.standard())
+                    MIGRAPHX_THROW("MLIR doesnt support non-standard output");
+                return s;
             }
             std::vector<shape> input_shapes;
             input_shapes.resize(ins->inputs().size());
@@ -119,28 +112,107 @@ struct mlir_op
 MIGRAPHX_REGISTER_OP(mlir_op);
 
 namespace {
+std::tuple<instruction_ref, std::vector<instruction_ref>>
+fuse_input_ops_and_gemm_based_op(module_ref mm, instruction_ref gemm_based_op)
+{
+    std::vector<instruction_ref> top_inputs;
+    std::vector<instruction_ref> imm_inputs;
+    size_t input_cnt = 0;
+    for(instruction_ref input : gemm_based_op->inputs())
+    {
+        std::vector<operation> op_stream;
+        while(contains(
+            {"slice", "transpose", "contiguous", "reshape", "squeeze", "flatten", "unsqueeze"},
+            input->name()))
+        {
+            operation op = input->get_operator();
+            if(contains({"squeeze", "flatten", "unsqueeze"}, input->name()))
+            {
+                op = migraphx::make_op("reshape", {{"dims", input->get_shape().lens()}});
+            }
+            op_stream.push_back(op);
+            input = input->inputs().at(0);
+        }
+        top_inputs.push_back(input);
+        instruction_ref prev_input =
+            mm->add_parameter("y" + std::to_string(input_cnt++), input->get_shape());
+        for(const auto& op : reverse(op_stream))
+        {
+            prev_input = mm->add_instruction(op, {prev_input});
+        }
+        imm_inputs.push_back(prev_input);
+    }
+    instruction_ref new_gemm_based_op =
+        mm->add_instruction(gemm_based_op->get_operator(), imm_inputs);
+    return {new_gemm_based_op, top_inputs};
+}
 
-MIGRAPHX_PRED_MATCHER(is_mlir_conv, instruction_ref ins)
+enum class mlir_mode
 {
-    if(ins->name() != "convolution" and ins->name() != "quant_convolution")
-        return false;
-    value v    = ins->get_operator().to_value();
-    auto group = v.at("group").to<int>();
-    if(group != 1)
-        return false;
-    // Avoid MLIR assertion: Index < Length && "Invalid index!"
-    if(ins->get_shape().lens().size() != 4)
-        return false;
-    return true;
+    all,
+    fast,
+    int8,
+    none
+};
+
+auto is_mlir_dot(mlir_mode mode)
+{
+    return match::make_basic_pred_matcher([=](instruction_ref ins) {
+        if(mode == mlir_mode::none)
+            return false;
+        if(ins->name() != "dot" and ins->name() != "quant_dot")
+            return false;
+        if(mode != mlir_mode::fast)
+            return true;
+        auto a = ins->inputs().front()->get_shape();
+        auto b = ins->inputs().back()->get_shape();
+        // auto m = a.lens()[a.lens().size() - 2];
+        // auto n = b.lens().back();
+        auto k = a.lens().back();
+        // Skipping GEMMs with a K dimension greater than 2048 is a course-grained strategy
+        // to avoid poor-performing GEMM kernels from MLIR
+        // To-do: Investigate a more precise strategy
+        return k <= 2048;
+    });
 }
 
-struct find_mlir_op
+auto is_mlir_conv(mlir_mode mode)
 {
+    return match::make_basic_pred_matcher([=](instruction_ref ins) {
+        if(mode == mlir_mode::none)
+            return false;
+        if(ins->name() != "convolution" and ins->name() != "quant_convolution")
+            return false;
+        value v    = ins->get_operator().to_value();
+        auto group = v.at("group").to<int>();
+        if(group != 1)
+            return false;
+        // Avoid MLIR assertion: Index < Length && "Invalid index!"
+        if(ins->get_shape().lens().size() != 4)
+            return false;
+        if(ins->get_shape().type() == shape::int8_type)
+            return true;
+        if(mode == mlir_mode::int8)
+            return false;
+        if(mode == mlir_mode::all)
+            return true;
+        auto w = ins->inputs().at(1)->get_shape();
+        if(w.lens().size() != 4)
+            return true;
+        if(w.lens()[2] != w.lens()[3])
+            return true;
+        return (w.lens()[3] % 3) != 0;
+    });
+}
+
+struct find_mlir_fused_ops
+{
+    mlir_mode conv_mode = mlir_mode::none;
+    mlir_mode dot_mode  = mlir_mode::none;
     auto matcher() const
     {
         auto dot_or_conv = match::skip(match::name("contiguous"))(
-            match::any_of(match::name("dot"), match::name("quant_dot"), is_mlir_conv())
-                .bind("gemm_based_op"));
+            match::any_of(is_mlir_dot(dot_mode), is_mlir_conv(conv_mode)).bind("gemm_based_op"));
         return match::name("pointwise")(match::any_of[match::inputs()](dot_or_conv.bind("x")));
     }
 
@@ -163,34 +235,6 @@ struct find_mlir_op
         return ins_map;
     }
 
-    std::tuple<instruction_ref, std::vector<instruction_ref>>
-    fuse_input_ops_and_gemm_based_op(module_ref mm, instruction_ref gemm_based_op) const
-    {
-        std::vector<instruction_ref> top_inputs;
-        std::vector<instruction_ref> imm_inputs;
-        size_t input_cnt = 0;
-        for(instruction_ref input : gemm_based_op->inputs())
-        {
-            std::vector<operation> op_stream;
-            while(contains({"slice", "transpose", "contiguous", "reshape"}, input->name()))
-            {
-                op_stream.push_back(input->get_operator());
-                input = input->inputs().at(0);
-            }
-            top_inputs.push_back(input);
-            instruction_ref prev_input =
-                mm->add_parameter("y" + std::to_string(input_cnt++), input->get_shape());
-            for(const auto& op : reverse(op_stream))
-            {
-                prev_input = mm->add_instruction(op, {prev_input});
-            }
-            imm_inputs.push_back(prev_input);
-        }
-        instruction_ref new_gemm_based_op =
-            mm->add_instruction(gemm_based_op->get_operator(), imm_inputs);
-        return {new_gemm_based_op, top_inputs};
-    }
-
     // Whitelist supported fusion options, including imposing type constraints
     // for cases where MLIR only supports an operation (usually a pointwise function)
     // on particular types.
@@ -236,8 +280,7 @@ struct find_mlir_op
             "log",
             "recip",
             "rsqrt",
-            // There are bugs in MLIR right now for models using sigmoid so disable it for now
-            // "sigmoid",
+            "sigmoid",
             "softmax",
             "tanh",
         };
@@ -282,9 +325,9 @@ struct find_mlir_op
                        names.end(),
                        ins->inputs().begin(),
                        std::inserter(param_map, param_map.end()),
-                       [&, &anchor_op = anchor_op](auto name, auto input) {
+                       [&, &anchor = anchor_op](auto name, auto input) {
                            if(input == x_ins)
-                               return std::make_pair(pm->get_parameter(name), anchor_op);
+                               return std::make_pair(pm->get_parameter(name), anchor);
                            return std::make_pair(pm->get_parameter(name),
                                                  mm->add_parameter(name, input->get_shape()));
                        });
@@ -301,20 +344,91 @@ struct find_mlir_op
     }
 };
 
+template <auto Matcher>
+struct find_mlir_standalone_op
+{
+    mlir_mode mode = mlir_mode::none;
+    auto matcher() const { return Matcher(mode); }
+    void apply(module_pass_manager& mpm, const match::matcher_result& r) const
+    {
+        auto conv_based_op = r.result;
+        // enable only for fp32/fp16/i8 types
+        if(std::any_of(conv_based_op->inputs().begin(), conv_based_op->inputs().end(), [&](auto i) {
+               return not contains(
+                   {shape::type_t::float_type, shape::type_t::half_type, shape::type_t::int8_type},
+                   i->get_shape().type());
+           }))
+            return;
+
+        static size_t counter = 0;
+        module_ref mm =
+            mpm.create_module("mlir_" + conv_based_op->name() + std::to_string(counter++));
+        mm->set_bypass();
+        auto [anchor_op, top_inputs] = fuse_input_ops_and_gemm_based_op(mm, conv_based_op);
+        mm->add_return({anchor_op});
+        mpm.get_module().replace_instruction(
+            conv_based_op, mlir_op{conv_based_op->get_operator()}, top_inputs, {mm});
+    }
+};
+
+using find_mlir_standalone_convolution_op = find_mlir_standalone_op<&is_mlir_conv>;
+using find_mlir_standalone_dot_op         = find_mlir_standalone_op<&is_mlir_dot>;
+
+/**
+ * @brief Declares a new MIGraphX environment variable which forces to generate
+ * only specific MLIR operations.
+ *
+ * The variable, if defined, forces MIGraphX to use only specific operations
+ * with MLIR regardless of the underlying GPU architecture. The variable accepts
+ * a list of operations separated by comma. The variable recognizes the following
+ * operations: "fused", "convolution", "dot". If the variable is not defined MIGraphX
+ * will decide by itself which operations to delegate to MLIR. The variable is
+ * intended to be primarily used by rocMLIR developers.
+ */
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_MLIR_USE_SPECIFIC_OPS);
+
+bool is_requested(std::string_view option, bool fallback = false)
+{
+    auto string_value  = string_value_of(MIGRAPHX_MLIR_USE_SPECIFIC_OPS{}, "");
+    if(string_value.empty())
+        return fallback;
+    const auto options = split_string(string_value, ',');
+    return contains(options, option);
+}
 } // namespace
 
-#endif
+#endif // MIGRAPHX_MLIR
 
 void fuse_mlir::apply(module_pass_manager& mpm) const
 {
 #ifdef MIGRAPHX_MLIR
-    match::find_matches(mpm, find_mlir_op{});
+    const auto& device_name = ctx == nullptr ? "" : ctx->get_current_device().get_gfx_name();
+    const bool is_navi      = starts_with(device_name, "gfx110");
+
+    auto get_mode = [&](std::string_view option, mlir_mode m1, mlir_mode m2 = mlir_mode::fast) {
+        if(is_requested(option))
+            return mlir_mode::all;
+        if(is_navi)
+            return mlir_mode::all;
+        return std::max(m1, m2);
+    };
+
+    mlir_mode mode =
+        (enabled(MIGRAPHX_ENABLE_EXTRA_MLIR{}) or enable_extra) ? mlir_mode::fast : mlir_mode::none;
+
+    match::find_matches(mpm,
+                        find_mlir_fused_ops{.conv_mode = get_mode("fused", mlir_mode::fast),
+                                            .dot_mode  = get_mode("fused", mode)});
+
+    match::find_matches(
+        mpm,
+        find_mlir_standalone_convolution_op{get_mode("convolution", mlir_mode::int8)},
+        find_mlir_standalone_dot_op{get_mode("dot", mlir_mode::none)});
 #else
     (void)mpm;
 #endif
 }
 
 } // namespace gpu
-
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/targets/gpu/fuse_ops.cpp

@@ -790,22 +790,26 @@ struct find_layernorm_pointwise
 {
     auto matcher() const
     {
-        return precompile_name("pointwise")(match::arg(0)(
+        return precompile_name("pointwise")(match::any_of[match::inputs()](
             precompile_name("gpu::prelayernorm", "gpu::preadd_layernorm").bind("layernorm")));
     }
 
     void apply(module& m, const match::matcher_result& r) const
     {
-        auto ins       = r.result;
+        auto pw_ins    = r.result;
         auto layernorm = r.instructions["layernorm"];
         if(not layernorm->module_inputs().empty())
             return;
-        auto* pm    = ins->module_inputs().front();
+        auto* pm       = pw_ins->module_inputs().front();
+        auto pw_inputs = pw_ins->inputs();
+        auto ln_pos    = std::find(pw_inputs.begin(), pw_inputs.end(), layernorm);
+        assert(ln_pos != pw_inputs.end());
+        pw_inputs.erase(ln_pos);
         auto inputs = layernorm->inputs();
         inputs.pop_back();
-        inputs.insert(inputs.end(), ins->inputs().begin() + 1, ins->inputs().end());
+        inputs.insert(inputs.end(), pw_inputs.begin(), pw_inputs.end());
 
-        m.replace_instruction(ins, layernorm->get_operator(), inputs, {pm});
+        m.replace_instruction(pw_ins, layernorm->get_operator(), inputs, {pm});
     }
 };
 

src/targets/gpu/hiprtc/main.cpp

@@ -27,6 +27,7 @@
 #include <migraphx/msgpack.hpp>
 #include <migraphx/file_buffer.hpp>
 #include <migraphx/ranges.hpp>
+#include <array>
 #include <iostream>
 #include <cstring>
 

src/targets/gpu/include/migraphx/gpu/ck.hpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+#ifndef MIGRAPHX_GUARD_GPU_CK_HPP
+#define MIGRAPHX_GUARD_GPU_CK_HPP
+
+#include <migraphx/compile_src.hpp>
+#include <migraphx/env.hpp>
+#include <migraphx/shape.hpp>
+#include <migraphx/stringutils.hpp>
+#include <string_view>
+
+#include "ck/host/device_gemm_multiple_d.hpp"
+#include "ck/host/device_batched_gemm_softmax_gemm.hpp"
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+#ifndef _WIN32
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_CK);
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_LOG_CK_GEMM);
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_CK_DEBUG);
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_TUNE_CK);
+#endif
+
+// NOLINTNEXTLINE
+const char* const disable_warning_pragma = R"__migraphx__(
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Weverything"
+${content}
+#pragma clang diagnostic pop
+)__migraphx__";
+
+template <class P>
+std::string ck_disable_warnings(P p)
+{
+    return interpolate_string(disable_warning_pragma,
+                              {{"content", std::string{p.data(), p.size()}}});
+}
+
+static std::unordered_map<std::string, std::string> create_ck_header_strings()
+{
+    std::unordered_map<std::string, std::string> result;
+    auto ck_headers = ck::host::GetHeaders();
+
+    std::transform(
+        ck_headers.begin(), ck_headers.end(), std::inserter(result, result.begin()), [&](auto& p) {
+            return std::pair<std::string, std::string>(p.first, ck_disable_warnings(p.second));
+        });
+    return result;
+}
+
+static std::vector<src_file> create_ck_headers()
+{
+    static const auto& header_strings = create_ck_header_strings();
+    std::vector<src_file> srcs;
+    std::transform(header_strings.begin(),
+                   header_strings.end(),
+                   std::back_inserter(srcs),
+                   [&](auto& p) { return src_file{p}; });
+    return srcs;
+}
+
+static inline const std::vector<src_file>& ck_headers()
+{
+    static const auto& headers = create_ck_headers();
+    return headers;
+}
+
+inline bool transposed_matrix(const shape& s) { return s.strides().back() != 1; }
+
+inline ck::host::DataType get_type(const shape& s)
+{
+    if(s.type() == shape::half_type)
+        return ck::host::DataType::Half;
+    else if(s.type() == shape::float_type)
+        return ck::host::DataType::Float;
+    else if(s.type() == shape::int8_type)
+        return ck::host::DataType::Int8;
+    else if(s.type() == shape::int32_type)
+        return ck::host::DataType::Int32;
+    MIGRAPHX_THROW("Unsupported ck type");
+}
+
+inline std::size_t get_batch_count(const shape& s)
+{
+    return std::accumulate(
+        s.lens().rbegin() + 2, s.lens().rend(), std::size_t{1}, std::multiplies<std::size_t>());
+}
+
+inline void fold_batch_dims(shape& s)
+{
+    auto lens = s.lens();
+    if(lens.size() <= 2)
+        return;
+    auto batch_count = get_batch_count(s);
+    auto m1          = lens.at(lens.size() - 2);
+    auto m2          = lens.at(lens.size() - 1);
+    if(transposed_matrix(s))
+        s = shape{s.type(), {m1, m2 * batch_count}};
+    else
+        s = shape{s.type(), {m1 * batch_count, m2}};
+}
+
+inline void remove_batch_dims(shape& s)
+{
+    auto lens = s.lens();
+    if(lens.size() <= 2)
+        return;
+    auto m1 = lens.at(lens.size() - 2);
+    auto m2 = lens.at(lens.size() - 1);
+    s       = shape{s.type(), {m1, m2}};
+}
+
+inline bool standard_batch(const shape& s)
+{
+    if(s.lens().size() < 3)
+        return true;
+    std::vector<std::size_t> lens(s.lens().begin(), s.lens().end() - 2);
+    std::vector<std::size_t> strides(s.strides().begin(), s.strides().end() - 2);
+    auto base = *(s.lens().end() - 2) * *(s.lens().end() - 1);
+    std::transform(strides.begin(), strides.end(), strides.begin(), [&](auto stride) {
+        return stride / base;
+    });
+    return shape{s.type(), lens, strides}.standard();
+}
+
+inline bool can_fold_batch(const std::vector<shape>& inputs)
+{
+    const auto& b_shape = inputs[1];
+    if(std::any_of(inputs.begin() + 2, inputs.end() - 1, [](auto input) {
+           return not standard_batch(input);
+       }))
+        return false;
+    const auto& b_strides = b_shape.strides();
+    return std::all_of(
+        b_strides.begin(), b_strides.end() - 2, [](auto stride) { return stride == 0; });
+}
+
+} // namespace gpu
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+#endif // MIGRAPHX_GUARD_GPU_CK_HPP

src/targets/gpu/include/migraphx/gpu/compile_hip.hpp

@@ -45,10 +45,7 @@ MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_HIPRTC_WORKAROUNDS);
 struct hiprtc_src_file
 {
     hiprtc_src_file() = default;
-    hiprtc_src_file(const src_file& s)
-        : path(s.path.string()), content(s.content.first, s.content.second)
-    {
-    }
+    hiprtc_src_file(const src_file& s) : path(s.path.string()), content(s.content) {}
     std::string path;
     std::string content;
     template <class Self, class F>
@@ -58,6 +55,8 @@ struct hiprtc_src_file
     }
 };
 
+MIGRAPHX_GPU_EXPORT bool hip_has_flags(const std::vector<std::string>& flags);
+
 MIGRAPHX_GPU_EXPORT std::vector<std::vector<char>> compile_hip_src_with_hiprtc(
     std::vector<hiprtc_src_file> srcs, std::string params, const std::string& arch);
 

src/targets/gpu/include/migraphx/gpu/context.hpp

@@ -299,23 +299,6 @@ struct context
 
     any_ptr get_queue() { return get_stream().get(); }
 
-    void enable_perf_measurement(bool b = true)
-    {
-        if(b)
-        {
-            start_event = create_event_for_timing();
-            stop_event  = create_event_for_timing();
-            get_stream().record(start_event.get());
-            get_stream().record(stop_event.get());
-        }
-        else
-        {
-            start_event = nullptr;
-            stop_event  = nullptr;
-        }
-        measure_perf = b;
-    }
-
     std::pair<hipEvent_t, hipEvent_t> get_perf_events() const
     {
         if(measure_perf)
@@ -323,12 +306,12 @@ struct context
         return std::make_pair(nullptr, nullptr);
     }
 
-    float get_elapsed_ms() const
+    static float get_elapsed_ms(hipEvent_t start, hipEvent_t stop)
     {
         float result = 0;
-        if(start_event != nullptr and stop_event != nullptr)
+        if(start != nullptr and stop != nullptr)
         {
-            auto status = hipEventElapsedTime(&result, start_event.get(), stop_event.get());
+            auto status = hipEventElapsedTime(&result, start, stop);
             if(status != hipSuccess)
                 MIGRAPHX_THROW("Failed hipEventElapsedTime: " + hip_error(status));
         }

src/targets/gpu/include/migraphx/gpu/convolution.hpp

@@ -84,8 +84,10 @@ struct miopen_convolution
     {
         check_shapes{inputs, op}.has(4);
         std::vector<shape> conv_inputs(inputs.begin(), inputs.begin() + 2);
-        check_shapes{conv_inputs, *this}.max_ndims(5).packed_layouts(
-            {{0, 1, 2}, {0, 1, 2, 3}, {0, 2, 3, 1}, {0, 1, 2, 3, 4}});
+        check_shapes{conv_inputs, *this}
+            .max_ndims(5)
+            .packed_layouts({{0, 1, 2}, {0, 1, 2, 3}, {0, 2, 3, 1}, {0, 1, 2, 3, 4}})
+            .same_layout();
         return migraphx::compute_shape<Op>(op, conv_inputs);
     }
 
@@ -197,9 +199,9 @@ struct miopen_convolution
             // MIOpen has APIs to pass pre-allocated buffers starting from rocm-5.6
             preallocate = true;
 #endif
-            auto x = preallocate ? to_gpu(generate_argument(x_shape)) : inputs[0];
-            auto w = preallocate ? to_gpu(generate_argument(w_shape)) : inputs[1];
-            auto y = preallocate ? allocate_gpu(output_shape) : inputs[2];
+            auto x = preallocate ? to_gpu(generate_argument(x_shape)) : argument{inputs[0]};
+            auto w = preallocate ? to_gpu(generate_argument(w_shape)) : argument{inputs[1]};
+            auto y = preallocate ? allocate_gpu(output_shape) : argument{inputs[2]};
             auto workspace =
                 preallocate ? allocate_gpu(workspace_shape) : migraphx::argument(workspace_shape);
 

src/targets/gpu/include/migraphx/gpu/device/arg_op.hpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to deal
@@ -55,7 +55,7 @@ MIGRAPHX_DEVICE_CONSTEXPR val_index<T> make_val_index(T v, int64_t i)
     return {v, i};
 }
 
-struct argmax_op
+struct argmax_op_first_index
 {
     template <class T>
     MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
@@ -73,7 +73,25 @@ struct argmax_op
     MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return lowest(); }
 };
 
-struct argmin_op
+struct argmax_op_last_index
+{
+    template <class T>
+    MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
+    {
+        if(x.val > y.val)
+            return x;
+        else if(x.val < y.val)
+            return y;
+        else
+        {
+            return (x.index > y.index) ? x : y;
+        }
+    }
+
+    MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return lowest(); }
+};
+
+struct argmin_op_first_index
 {
     template <class T>
     MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
@@ -91,6 +109,24 @@ struct argmin_op
     MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return highest(); }
 };
 
+struct argmin_op_last_index
+{
+    template <class T>
+    MIGRAPHX_DEVICE_CONSTEXPR val_index<T> operator()(val_index<T> x, val_index<T> y) const
+    {
+        if(x.val < y.val)
+            return x;
+        else if(x.val > y.val)
+            return y;
+        else
+        {
+            return (x.index > y.index) ? x : y;
+        }
+    }
+
+    MIGRAPHX_DEVICE_CONSTEXPR auto init() const { return highest(); }
+};
+
 template <class Op>
 void arg_op(Op op, hipStream_t stream, const argument& result, const argument& arg, int64_t axis)
 {

src/targets/gpu/include/migraphx/gpu/device/argmax.hpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to deal
@@ -36,7 +36,8 @@ namespace device {
 void MIGRAPHX_DEVICE_EXPORT argmax(hipStream_t stream,
                                    const argument& result,
                                    const argument& arg,
-                                   int64_t axis);
+                                   int64_t axis,
+                                   bool select_last_index);
 
 } // namespace device
 } // namespace gpu

src/targets/gpu/include/migraphx/gpu/device/argmin.hpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to deal
@@ -36,7 +36,8 @@ namespace device {
 void MIGRAPHX_DEVICE_EXPORT argmin(hipStream_t stream,
                                    const argument& result,
                                    const argument& arg,
-                                   int64_t axis);
+                                   int64_t axis,
+                                   bool select_last_index);
 
 } // namespace device
 } // namespace gpu

src/targets/gpu/include/migraphx/gpu/fuse_mlir.hpp

@@ -38,6 +38,7 @@ MIGRAPHX_GPU_EXPORT bool mlir_enabled();
 struct MIGRAPHX_GPU_EXPORT fuse_mlir
 {
     context* ctx = nullptr;
+    bool enable_extra = false;
     std::string name() const { return "gpu::fuse_mlir"; }
     void apply(module_pass_manager& mpm) const;
 };

src/targets/gpu/include/migraphx/gpu/fuse_ops.hpp

@@ -24,7 +24,6 @@
 #ifndef MIGRAPHX_GUARD_RTGLIB_FUSE_OPS_HPP
 #define MIGRAPHX_GUARD_RTGLIB_FUSE_OPS_HPP
 
-#include <migraphx/config.hpp>
 #include <migraphx/gpu/context.hpp>
 
 namespace migraphx {
@@ -34,7 +33,7 @@ struct module;
 
 namespace gpu {
 
-struct fuse_ops
+struct MIGRAPHX_GPU_EXPORT fuse_ops
 {
     context* ctx   = nullptr;
     bool fast_math = true;

src/targets/gpu/include/migraphx/gpu/gemm_softmax_gemm.hpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+#ifndef MIGRAPHX_GUARD_GPU_GEMM_SOFTMAX_GEMM_HPP
+#define MIGRAPHX_GUARD_GPU_GEMM_SOFTMAX_GEMM_HPP
+
+#include <migraphx/make_op.hpp>
+#include <migraphx/check_shapes.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct gemm_softmax_gemm
+{
+    operation op = make_op("dot");
+    float scale  = 1.0;
+
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
+    {
+        return pack(f(self.op, "op"), f(self.scale, "scale"));
+    }
+
+    std::string name() const { return "gpu::gemm_softmax_gemm"; }
+
+    void check_gemm_shape(const shape& s) const
+    {
+        if(not contains(range(s.strides().rbegin(), s.strides().rbegin() + 3), 1))
+            MIGRAPHX_THROW("Invalid shape for " + name());
+    }
+
+    shape compute_shape(std::vector<shape> inputs, const std::vector<module_ref>&) const
+    {
+        check_shapes{inputs, *this}.same_ndims();
+        if(inputs.size() < 3)
+            MIGRAPHX_THROW(name() + ": Expected 3 inputs but got " + to_string(inputs.size()));
+        auto a  = inputs[0];
+        auto b  = inputs[1];
+        auto b1 = inputs[2];
+        for(const auto& input : inputs)
+        {
+            check_gemm_shape(input);
+        }
+        return op.compute_shape({op.compute_shape({a, b}), b1});
+    }
+
+    static bool is_ck_supported_type(shape::type_t t) { return contains({shape::half_type}, t); }
+};
+
+} // namespace gpu
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+#endif // MIGRAPHX_GUARD_GPU_GEMM_SOFTMAX_GEMM_HPP

src/targets/gpu/include/migraphx/gpu/mlir.hpp

@@ -49,7 +49,8 @@ MIGRAPHX_GPU_EXPORT instruction_ref insert_mlir(module& m,
 
 MIGRAPHX_GPU_EXPORT tuning_config get_tuning_config_mlir(const context& migraphx_ctx,
                                                          module m,
-                                                         const std::vector<shape>& inputs);
+                                                         const std::vector<shape>& inputs,
+                                                         bool exhaustive);
 
 } // namespace gpu
 } // namespace MIGRAPHX_INLINE_NS

src/targets/gpu/include/migraphx/gpu/prefuse_ops.hpp

@@ -24,7 +24,7 @@
 #ifndef MIGRAPHX_GUARD_GPU_PREFUSE_OPS_HPP
 #define MIGRAPHX_GUARD_GPU_PREFUSE_OPS_HPP
 
-#include <migraphx/config.hpp>
+#include <migraphx/gpu/config.hpp>
 #include <string>
 
 namespace migraphx {
@@ -34,7 +34,7 @@ struct module_pass_manager;
 
 namespace gpu {
 
-struct prefuse_ops
+struct MIGRAPHX_GPU_EXPORT prefuse_ops
 {
     std::string name() const { return "gpu::prefuse_ops"; }
     void apply(module_pass_manager& mpm) const;

src/targets/gpu/include/migraphx/gpu/time_op.hpp

@@ -32,7 +32,7 @@ namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace gpu {
 
-MIGRAPHX_GPU_EXPORT std::pair<double, double>
+MIGRAPHX_GPU_EXPORT double
 time_op(context& ictx, operation op, const std::vector<shape>& inputs, int n = 100);
 
 } // namespace gpu