#pragma once #include #include #include #include #include #include #include #include #include #include #include #include #include namespace offcache { // execution policy selects in which way the data is supposed to be cached // and returned with the following behaviour is guaranteed in addition to the // returned value being valid: // Immediate: return as fast as possible // may return cached data, can return data in RAM // will trigger caching of the data provided // ImmediateNoCache: return as fast as possible and never trigger caching // same as Immediate but will not trigger caching // Relaxed: no rapid return needed, take time // will trigger caching and may only return // once the caching is successful but can still // provide data in RAM enum class ExecutionPolicy { Relaxed, Immediate, ImmediateNoCache }; class Cache; // the cache task structure will be used to submit and // control a cache element, while providing source pointer // and size in bytes for submission // // then the submitting thread may wait on the atomic "result" // which will be notified by the cache worker upon processing // after which the atomic-bool-ptr active will also become valid class CacheData { public: using dml_handler = dml::handler>; private: uint8_t* src_; size_t size_; std::atomic* active_; protected: std::atomic* cache_; uint8_t* incomplete_cache_; std::unique_ptr> handlers_; friend Cache; public: CacheData(uint8_t* data, const size_t size); CacheData(const CacheData& other); ~CacheData(); void Deallocate(); void WaitOnCompletion(); uint8_t* GetDataLocation() const; bool Active() const; }; // singleton which holds the cache workers // and is the place where work will be submited class Cache { public: // cache policy is defined as a type here to allow flexible usage of the cacher // given a numa destination node (where the data will be needed), the numa source // node (current location of the data) and the data size, this function should // return optimal cache placement // dst node and returned value can differ if the system, for example, has HBM // attached accessible directly to node n under a different node id m typedef int (CachePolicy)(const int numa_dst_node, const int numa_src_node, const size_t data_size); // copy policy specifies the copy-executing nodes for a given task // which allows flexibility in assignment for optimizing raw throughput // or choosing a conservative usage policy typedef std::vector (CopyPolicy)(const int numa_dst_node, const int numa_src_node); private: std::shared_mutex cache_mutex_; std::unordered_map cache_state_; CachePolicy* cache_policy_function_ = nullptr; CopyPolicy* copy_policy_function_ = nullptr; dml::handler> ExecuteCopy(const uint8_t* src, uint8_t* dst, const size_t size, const int node) const; void SubmitTask(CacheData* task); public: void Init(CachePolicy* cache_policy_function, CopyPolicy* copy_policy_function); // function to perform data access through the cache // behaviour depends on the chosen execution policy // Immediate and ImmediateNoCache return a cache task // with guaranteed-valid result value where Relaxed // policy does not come with this guarantee. std::unique_ptr Access(uint8_t* data, const size_t size, const ExecutionPolicy policy); void Flush(); }; } inline void offcache::Cache::Init(CachePolicy* cache_policy_function, CopyPolicy* copy_policy_function) { cache_policy_function_ = cache_policy_function; copy_policy_function_ = copy_policy_function; // initialize numa library numa_available(); std::cout << "[-] Cache Initialized" << std::endl; } inline std::unique_ptr offcache::Cache::Access(uint8_t* data, const size_t size, const ExecutionPolicy policy) { // the best situation is if this data is already cached // which we check in an unnamed block in which the cache // is locked for reading to prevent another thread // from marking the element we may find as unused and // clearing it { std::shared_lock lock(cache_mutex_); const auto search = cache_state_.find(data); if (search != cache_state_.end()) { if (search->second.size_ == size) { search->second.active_->store(true); std::cout << "[+] Found Cached version for 0x" << std::hex << (uint64_t)data << std::dec << std::endl; return std::move(std::make_unique(search->second)); } else { std::cout << "[!] Found Cached version with size missmatch for 0x" << std::hex << (uint64_t)data << std::dec << std::endl; cache_state_.erase(search); } } } // at this point the requested data is not present in cache // and we create a caching task for it auto task = std::make_unique(data, size); if (policy == ExecutionPolicy::Immediate) { // in intermediate mode the returned task // object is guaranteed to be valid and therefore // its resulting location must be validated // after which we submit the task // maybe_result is then set by submit task->cache_->store(data); SubmitTask(task.get()); return std::move(task); } else if (policy == ExecutionPolicy::ImmediateNoCache) { // for immediatenocache we just validate // the generated task and return it // we must also set maybe_result in case // someone waits on this task->cache_->store(data); task->incomplete_cache_ = data; return std::move(task); } else if (policy == ExecutionPolicy::Relaxed) { // for relaxed no valid task must be returned // and therefore we just submit and then give // the possible invalid task back with only // maybe_result set by submission SubmitTask(task.get()); return std::move(task); } else { // this should not be reached } } inline void offcache::Cache::SubmitTask(CacheData* task) { // obtain numa node of current thread to determine where the data is needed const int current_cpu = sched_getcpu(); const int current_node = numa_node_of_cpu(current_cpu); // obtain node that the given data pointer is allocated on int data_node = -1; get_mempolicy(&data_node, NULL, 0, (void*)task->src_, MPOL_F_NODE | MPOL_F_ADDR); // querry cache policy function for the destination numa node const int dst_node = cache_policy_function_(current_node, data_node, task->size_); std::cout << "[+] Allocating " << task->size_ << "B on node " << dst_node << " for " << std::hex << (uint64_t)task->src_ << std::dec << std::endl; // allocate data on this node and flush the unused parts of the // cache if the operation fails and retry once // TODO: smarter flush strategy could keep some stuff cached uint8_t* dst = reinterpret_cast(numa_alloc_onnode(task->size_, dst_node)); if (dst == nullptr) { std::cout << "[!] First allocation try failed for " << task->size_ << "B on node " << dst_node << std::endl; Flush(); dst = reinterpret_cast(numa_alloc_onnode(task->size_, dst_node)); if (dst == nullptr) { std::cout << "[x] Second allocation try failed for " << task->size_ << "B on node " << dst_node << std::endl; return; } } task->incomplete_cache_ = dst; // querry copy policy function for the nodes to use for the copy const std::vector executing_nodes = copy_policy_function_(dst_node, data_node); const size_t task_count = executing_nodes.size(); // each task will copy one fair part of the total size // and in case the total size is not a factor of the // given task count the last node must copy the remainder const size_t size = task->size_ / task_count; const size_t last_size = size + task->size_ % task_count; // save the current numa node mask to restore later // as executing the copy task will place this thread // on a different node bitmask* nodemask = numa_get_run_node_mask(); for (uint32_t i = 0; i < task_count; i++) { const size_t local_size = i + 1 == task_count ? size : last_size; const size_t local_offset = i * size; const uint8_t* local_src = task->src_ + local_offset; uint8_t* local_dst = dst + local_offset; task->handlers_->emplace_back(ExecuteCopy(local_src, local_dst, local_size, executing_nodes[i])); } // only at this point may the task be added to the control structure // because adding it earlier could cause it to be returned for an // access request while the handler-vector is not fully populated // which could cause the wait-function to return prematurely // TODO: this can be optimized because the abort is quite expensive { std::unique_lock lock(cache_mutex_); const auto state = cache_state_.insert({task->src_, *task}); // if state.second is false then no insertion took place // which means that concurrently whith this thread // some other thread must have accessed the same // resource in which case we must perform an abort // TODO: abort is not the only way to handle this situation if (!state.second) { std::cout << "[x] Found another cache instance for 0x" << std::hex << (uint64_t)task->src_ << std::dec << std::endl; // first wait on all copy operations to be completed task->WaitOnCompletion(); // abort by doing the following steps // (1) free the allocated memory, (2) remove the "maybe result" as // we will not run the caching operation, (3) clear the sub tasks // for the very same reason, (4) set the result to the RAM-location numa_free(dst, task->size_); task->incomplete_cache_ = nullptr; task->cache_->store(task->src_); std::cout << "[-] Abort completed for 0x" << std::hex << (uint64_t)task->src_ << std::dec << std::endl; return; } } // restore the previous nodemask numa_run_on_node_mask(nodemask); } inline dml::handler> offcache::Cache::ExecuteCopy(const uint8_t* src, uint8_t* dst, const size_t size, const int node) const { dml::const_data_view srcv = dml::make_view(src, size); dml::data_view dstv = dml::make_view(dst, size); numa_run_on_node(node); return dml::submit(dml::mem_copy.block_on_fault(), srcv, dstv); } inline void offcache::CacheData::WaitOnCompletion() { if (handlers_ == nullptr) { std::cout << "[-] Waiting on cache-var-update for CacheData 0x" << std::hex << (uint64_t)src_ << std::dec << std::endl; cache_->wait(nullptr); std::cout << "[+] Finished waiting on cache-var-update for CacheData 0x" << std::hex << (uint64_t)src_ << std::dec << std::endl; } else { std::cout << "[-] Waiting on handlers for CacheData 0x" << std::hex << (uint64_t)src_ << std::dec << std::endl; for (auto& handler : *handlers_) { auto result = handler.get(); // TODO: handle the returned status code } handlers_ = nullptr; std::cout << "[+] Finished waiting on handlers for CacheData 0x" << std::hex << (uint64_t)src_ << std::dec << std::endl; cache_->store(incomplete_cache_); cache_->notify_all(); } } offcache::CacheData::CacheData(uint8_t* data, const size_t size) { std::cout << "[-] New CacheData 0x" << std::hex << (uint64_t)data << std::dec << std::endl; src_ = data; size_ = size; active_ = new std::atomic(); cache_ = new std::atomic(); incomplete_cache_ = nullptr; handlers_ = std::make_unique>(); } offcache::CacheData::CacheData(const offcache::CacheData& other) { std::cout << "[-] Copy Created for CacheData 0x" << std::hex << (uint64_t)other.src_ << std::dec << std::endl; src_ = other.src_; size_ = other.size_; cache_ = other.cache_; active_ = other.active_; incomplete_cache_ = nullptr; handlers_ = nullptr; active_->fetch_add(1); } offcache::CacheData::~CacheData() { std::cout << "[-] Destructor for CacheData 0x" << std::hex << (uint64_t)src_ << std::dec << std::endl; const int32_t v = active_->fetch_sub(1); // if the returned value is non-positive // then we must execute proper deletion // as this was the last reference if (v <= 0) { std::cout << "[!] Full Destructor for CacheData 0x" << std::hex << (uint64_t)src_ << std::dec << std::endl; Deallocate(); delete active_; delete cache_; } } void offcache::CacheData::Deallocate() { std::cout << "[!] Deallocating for CacheData 0x" << std::hex << (uint64_t)src_ << std::dec << std::endl; numa_free(cache_, size_); cache_ = nullptr; incomplete_cache_ = nullptr; } uint8_t *offcache::CacheData::GetDataLocation() const { return cache_->load(); } bool offcache::CacheData::Active() const { return active_->load() > 0; } inline void offcache::Cache::Flush() { std::cout << "[-] Flushing Cache" << std::endl; // TODO: there is a better way to implement this flush { std::unique_lock lock(cache_mutex_); auto it = cache_state_.begin(); while (it != cache_state_.end()) { if (it->second.Active() == false) { cache_state_.erase(it); it = cache_state_.begin(); } else { it++; } } } }