diff --git a/paddle/phi/kernels/autotune/CMakeLists.txt b/paddle/phi/kernels/autotune/CMakeLists.txt
index c7bb30d2d767cfc712fc19152f35bb406a89eac9..d1579f66e29e064a90dde7ecb4eb6eb9cb62da45 100644
--- a/paddle/phi/kernels/autotune/CMakeLists.txt
+++ b/paddle/phi/kernels/autotune/CMakeLists.txt
@@ -3,3 +3,5 @@ if (WITH_GPU)
 elseif (WITH_ROCM)
     hip_test(gpu_timer_test SRCS gpu_timer_test.cu DEPS gtest)
 endif()
+
+cc_test(cache_test SRCS cache_test.cc DEPS gtest)
diff --git a/paddle/phi/kernels/autotune/cache.h b/paddle/phi/kernels/autotune/cache.h
new file mode 100644
index 0000000000000000000000000000000000000000..c5b068c28994d6a37dbf616af03d29a90ac14d9d
--- /dev/null
+++ b/paddle/phi/kernels/autotune/cache.h
@@ -0,0 +1,122 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+#include <algorithm>
+#include <mutex>
+#include <unordered_map>
+#include <vector>
+#include "glog/logging.h"
+#include "paddle/phi/common/data_type.h"
+#include "paddle/phi/core/enforce.h"
+#include "paddle/phi/core/errors.h"
+
+inline void HashCombine(std::size_t* seed) {}
+
+// combine hash value
+// https://stackoverflow.com/questions/2590677/how-do-i-combine-hash-values-in-c0x
+template <typename T, typename... Rest>
+inline void HashCombine(std::size_t* seed, const T& v, Rest... rest) {
+  std::hash<T> hasher;
+  *seed ^= hasher(v) + 0x9e3779b9 + (*seed << 6) + (*seed >> 2);
+  HashCombine(seed, rest...);
+}
+
+// custom specialization of std::hash can be injected in namespace std
+// ref: https://en.cppreference.com/w/cpp/utility/hash
+namespace std {
+template <typename T>
+struct hash<std::vector<T>> {
+  std::size_t operator()(std::vector<T> const& vec) const noexcept {
+    std::size_t seed = 0;
+    for (auto val : vec) {
+      HashCombine(&seed, val);
+    }
+    return seed;
+  }
+};
+}  // namespace std
+
+namespace phi {
+namespace autotune {
+
+template <typename AlgorithmT>
+class AlgorithmsCache {
+ public:
+  AlgorithmsCache() { hash_.clear(); }
+
+  template <typename... Args>
+  size_t GetKey(Args&&... args) {
+    size_t seed = 0;
+    HashCombine(&seed, std::forward<Args>(args)...);
+    return seed;
+  }
+
+  AlgorithmT Get(size_t key) {
+    std::lock_guard<std::mutex> lock(cache_mutex_);
+    PADDLE_ENFORCE_NE(
+        hash_.find(key),
+        hash_.end(),
+        phi::errors::PreconditionNotMet("The key does not exist."));
+    return hash_[key];
+  }
+
+  bool Find(size_t key) {
+    bool ret = false;
+    std::lock_guard<std::mutex> lock(cache_mutex_);
+    if (hash_.find(key) != hash_.end()) {
+      cache_hits_++;
+      ret = true;
+    } else {
+      cache_misses_++;
+    }
+    return ret;
+  }
+
+  void Set(size_t key, AlgorithmT algo) {
+    std::lock_guard<std::mutex> lock(cache_mutex_);
+    hash_[key] = algo;
+  }
+
+  float CacheHitRate() const {
+    int64_t num_accesses = cache_hits_ + cache_misses_;
+    float cache_hit_rate =
+        static_cast<float>(cache_hits_) / static_cast<float>(num_accesses);
+    return cache_hit_rate;
+  }
+
+  // Define the cache key of operator
+  size_t ConvKey(const std::vector<int64_t>& x_dims,
+                 const std::vector<int64_t>& w_dims,
+                 const std::vector<int>& strides,
+                 const std::vector<int>& paddings,
+                 const std::vector<int>& dilations,
+                 phi::DataType dtype) {
+    return GetKey(x_dims,
+                  w_dims,
+                  strides,
+                  paddings,
+                  dilations,
+                  static_cast<int64_t>(dtype));
+  }
+
+ private:
+  std::unordered_map<size_t, AlgorithmT> hash_;
+  std::mutex cache_mutex_;
+  int64_t cache_hits_ = 0;
+  int64_t cache_misses_ = 0;
+};
+
+}  // namespace autotune
+}  // namespace phi
diff --git a/paddle/phi/kernels/autotune/cache_test.cc b/paddle/phi/kernels/autotune/cache_test.cc
new file mode 100644
index 0000000000000000000000000000000000000000..b08a6cfc14ae887b1543aab219706df5997eb9d3
--- /dev/null
+++ b/paddle/phi/kernels/autotune/cache_test.cc
@@ -0,0 +1,45 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/phi/kernels/autotune/cache.h"
+#include <gtest/gtest.h>
+#include <cmath>
+#include <functional>
+#include "glog/logging.h"
+
+void Algo() { VLOG(3) << "algo test"; }
+
+TEST(AlgosCache, AlgosCache) {
+  phi::autotune::AlgorithmsCache<std::function<void()>> cache;
+  std::vector<int64_t> x_shape = {4, 224, 224, 3};
+  std::vector<int64_t> w_shape = {32, 3, 3, 3};
+  std::vector<int> paddings = {0, 0};
+  std::vector<int> strides = {2, 2};
+  std::vector<int> dilations = {1, 1};
+  phi::DataType dtype = paddle::experimental::CppTypeToDataType<float>::Type();
+
+  auto key =
+      cache.ConvKey(x_shape, w_shape, paddings, strides, dilations, dtype);
+  EXPECT_EQ(cache.Find(key), false);
+  cache.Set(key, Algo);
+  EXPECT_EQ(cache.Find(key), true);
+  auto algo = cache.Get(key);
+  algo();
+
+  x_shape = {4, 128, 128, 3};
+  key = cache.ConvKey(x_shape, w_shape, paddings, strides, dilations, dtype);
+  EXPECT_EQ(cache.Find(key), false);
+  float cache_hit_rate = static_cast<float>(1) / static_cast<float>(3);
+  EXPECT_LT(std::abs(cache_hit_rate - cache.CacheHitRate()), 1e-5);
+}