blob: 33564f426fb3842bfc6c212bc47b6d05e774b919 [file]
/*
* Copyright (C) 2019 The Android Open Source Project
*
* 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.
*/
#ifndef ANDROID_ML_NN_RUNTIME_EXECUTION_BURST_CONTROLLER_H
#define ANDROID_ML_NN_RUNTIME_EXECUTION_BURST_CONTROLLER_H
#include <android-base/macros.h>
#include <fmq/MessageQueue.h>
#include <hidl/MQDescriptor.h>
#include <atomic>
#include <map>
#include <memory>
#include <mutex>
#include <stack>
#include <tuple>
#include "HalInterfaces.h"
namespace android::nn {
using ::android::hardware::kSynchronizedReadWrite;
using ::android::hardware::MessageQueue;
using ::android::hardware::MQDescriptorSync;
using FmqRequestChannel = MessageQueue<FmqRequestDatum, kSynchronizedReadWrite>;
using FmqResultChannel = MessageQueue<FmqResultDatum, kSynchronizedReadWrite>;
/**
* Number of elements in the FMQ.
*/
constexpr const size_t kExecutionBurstChannelLength = 1024;
/**
* The ExecutionBurstController class manages both the serialization and
* deserialization of data across FMQ, making it appear to the runtime as a
* regular synchronous inference. Additionally, this class manages the burst's
* memory cache.
*/
class ExecutionBurstController {
DISALLOW_IMPLICIT_CONSTRUCTORS(ExecutionBurstController);
/**
* NN runtime burst callback object and memory cache.
*
* ExecutionBurstCallback associates a hidl_memory object with a slot number
* to be passed across FMQ. The ExecutionBurstServer can use this callback
* to retrieve this hidl_memory corresponding to the slot via HIDL.
*
* Whenever a hidl_memory object is copied, it will duplicate the underlying
* file descriptor. Because the NN runtime currently copies the hidl_memory
* on each execution, it is difficult to associate hidl_memory objects with
* previously cached hidl_memory objects. For this reason, callers of this
* class must pair each hidl_memory object with an associated key. For
* efficiency, if two hidl_memory objects represent the same underlying
* buffer, they must use the same key.
*/
class ExecutionBurstCallback : public IBurstCallback {
DISALLOW_COPY_AND_ASSIGN(ExecutionBurstCallback);
public:
ExecutionBurstCallback() = default;
Return<void> getMemories(const hidl_vec<int32_t>& slots, getMemories_cb cb) override;
std::vector<int32_t> getSlots(const hidl_vec<hidl_memory>& memories,
const std::vector<intptr_t>& keys);
int32_t getSlot(const hidl_memory& memory, intptr_t key);
/*
* This function performs two different actions:
* 1) Removes an entry from the cache (if present), including the local
* storage of the hidl_memory object. Note that this call does not
* free any corresponding hidl_memory object in ExecutionBurstServer,
* which is separately freed via IBurstContext::freeMemory.
* 2) Return whether a cache entry was removed and which slot was removed if
* found. If the key did not to correspond to any entry in the cache, a
* slot number of 0 is returned. The slot number and whether the entry
* existed is useful so the same slot can be freed in the
* ExecutionBurstServer's cache via IBurstContext::freeMemory.
*/
std::pair<bool, int32_t> freeMemory(intptr_t key);
private:
int32_t getSlotLocked(const hidl_memory& memory, intptr_t key);
int32_t allocateSlotLocked();
std::mutex mMutex;
std::stack<int32_t, std::vector<int32_t>> mFreeSlots;
std::map<intptr_t, int32_t> mMemoryIdToSlot;
std::vector<hidl_memory> mMemoryCache;
};
public:
/**
* Creates a burst controller on a prepared model.
*
* Prefer this over ExecutionBurstController's constructor.
*
* @param preparedModel Model prepared for execution to execute on.
* @param blocking 'true' if the FMQ should use a futex to perform blocking
* until data is available in a less responsive, but more energy
* efficient manner. 'false' if the FMQ should use spin-looping to
* wait until data is available in a more responsive, but less energy
* efficient manner.
* @return ExecutionBurstController Execution burst controller object.
*/
static std::unique_ptr<ExecutionBurstController> create(const sp<IPreparedModel>& preparedModel,
bool blocking);
ExecutionBurstController(std::unique_ptr<FmqRequestChannel> fmqRequestChannel,
std::unique_ptr<FmqResultChannel> fmqResultChannel,
const sp<IBurstContext>& burstContext,
const sp<ExecutionBurstCallback>& callback, bool blocking);
/**
* Execute a request on a model.
*
* @param request Arguments to be executed on a model.
* @param measure Whether to collect timing measurements, either YES or NO
* @param memoryIds Identifiers corresponding to each memory object in the
* request's pools.
* @return status and output shape of the execution and any execution time
* measurements.
*/
std::tuple<ErrorStatus, std::vector<OutputShape>, Timing> compute(
const Request& request, MeasureTiming measure, const std::vector<intptr_t>& memoryIds);
/**
* Propagate a user's freeing of memory to the service.
*
* @param key Key corresponding to the memory object.
*/
void freeMemory(intptr_t key);
private:
std::vector<FmqResultDatum> getPacketBlocking();
bool sendPacket(const std::vector<FmqRequestDatum>& packet);
std::vector<FmqRequestDatum> serialize(const Request& request, MeasureTiming measure,
const std::vector<intptr_t>& memoryIds);
std::tuple<ErrorStatus, std::vector<OutputShape>, Timing> deserialize(
const std::vector<FmqResultDatum>& data);
std::mutex mMutex;
const std::unique_ptr<FmqRequestChannel> mFmqRequestChannel;
const std::unique_ptr<FmqResultChannel> mFmqResultChannel;
const sp<IBurstContext> mBurstContext;
const sp<ExecutionBurstCallback> mMemoryCache;
const bool mUsesFutex;
};
} // namespace android::nn
#endif // ANDROID_ML_NN_RUNTIME_EXECUTION_BURST_CONTROLLER_H