feat(dtr): remove eviction threshold

GitOrigin-RevId: 35c2014bf3241d864db21b6e431158535442a672

imperative/python/megengine/dtr.py

@@ -114,6 +114,7 @@ def disable():
     r"""
     Stop recording computing path of tensors and performing DTR policy.
     """
+    _set_defrag(False)
     _set_option("enable_dtr_auto_drop", 0)
     _set_option("enable_drop", 0)
     _set_option("record_computing_path", 0)

imperative/src/impl/blob_manager_impl.cpp

@@ -156,6 +156,9 @@ void BlobManagerImpl::set_enable(bool flag) {
 }
 
 struct BlobManagerStub : BlobManager {
+    void alloc_direct(Blob* blob, size_t size) {
+        mgb_assert(0, "prohibited after global variable destruction");
+    };
     void alloc_with_defrag(Blob* blob, size_t size) {
         mgb_assert(0, "prohibited after global variable destruction");
     };

imperative/src/impl/blob_manager_impl.h

@@ -43,7 +43,7 @@ class BlobManagerImpl final: public BlobManager {
 
     void defrag(const CompNode& cn) override;
 
-    void alloc_direct(Blob* blob, size_t size);
+    void alloc_direct(Blob* blob, size_t size) override;
 
     DeviceTensorND alloc_workspace(CompNode cn, TensorLayout layout); 
 

imperative/src/impl/interpreter/interpreter_impl.cpp

@@ -20,6 +20,7 @@
 #include "megbrain/imperative/ops/opr_attr.h"
 #include "megbrain/imperative/utils/to_string.h"
 
+#include "../blob_manager_impl.h"
 #include "../event_pool.h"
 #include "../op_trait.h"
 
@@ -629,8 +630,9 @@ void ChannelImpl::do_apply_op(const ApplyOp& cmd) {
         tensor_inputs.push_back(i->ptr);
         input_memory_desc.push_back(i->mem_desc);
     }
-    // SmallVector<MemoryDesc> outputs_mem_desc;
-    // SmallVector<TensorPtr> tensor_outputs, workspaces;
+    if (state.options.enable_dtr_auto_drop && state.options.dtr_eviction_threshold > 0) {
+        auto_evict(0);
+    }
     auto [outputs_mem_desc, tensor_outputs, workspaces] = init_output_and_workspace(*cmd.op, tensor_inputs, input_memory_desc);
     if (outputs_mem_desc.size()) {
         for (size_t i = 0;i < outputs_mem_desc.size();i ++) {
@@ -682,9 +684,6 @@ void ChannelImpl::do_apply_op(const ApplyOp& cmd) {
     for (auto&& [device, kernel_id]: kernels) {
         RECORD_EVENT(KernelExecuteEvent, apply_id, kernel_id, Timer::record_event(device));
     }
-    if (state.options.enable_dtr_auto_drop && state.options.dtr_eviction_threshold > 0) {
-        auto_evict();
-    }
     // Apply op
     // Here std::move is REQUIRED for removing duplicated references.
     if (outputs_mem_desc.size()) {
@@ -752,29 +751,26 @@ void ChannelImpl::recompute(TensorInfo::ComputePath* path) {
     }
 }
 
-void ChannelImpl::auto_evict() {
+bool ChannelImpl::auto_evict(size_t force_num=0) {
     auto& state = get_worker_state();
     if (!m_dtr.comp_node.valid()) {
-        return;
+        return false;
     }
     size_t current_memory = m_dtr.comp_node.get_used_memory();
-    while (current_memory > state.options.dtr_eviction_threshold) {
+    size_t flag = false;
+    while ((state.options.dtr_eviction_threshold > 0 && current_memory > state.options.dtr_eviction_threshold) || force_num > 0) {
         RECORD_EVENT(AutoEvictEvent);
         sample_on_device(m_dtr.comp_node, false);
         auto best = m_dtr.find_best_tensor();
         if (!best) {
-            if (!m_dtr.warn_printed) {
-                m_dtr.warn_printed = true;
-                mgb_log_warn("No tensors on %s can be evicted automatically "
-                             "when memory usage is %.0lfMB. Maybe memory "
-                             "budget is too small.",
-                              m_dtr.comp_node.to_string().c_str(),
-                              current_memory / 1024.0 / 1024.0);
-            }
             break;
         }
         if (best->ptr.unique() && best->ptr->blob().unique()) {
             current_memory -= best->memory;
+            if (force_num > 0) {
+                force_num --;
+            }
+            flag = true;
         }
         do_drop(best);
         if (best->evict_type == EvictType::DROP) {
@@ -783,6 +779,7 @@ void ChannelImpl::auto_evict() {
         sample_on_device(m_dtr.comp_node, false);
         RECORD_EVENT(AutoEvictFinishEvent);
     }
+    return flag;
 }
 
 void ChannelImpl::detach_users(TensorInfo* dest) {
@@ -859,6 +856,41 @@ std::unordered_set<TensorInfo*> ChannelImpl::collect_valid_tensors() {
     return valid_tensors;
 }
 
+void ChannelImpl::alloc_tensor_with_evict(TensorPtr x) {
+    auto reserve_size = [&](size_t size) {
+        if (!m_dtr.comp_node.valid()) {
+            return false;
+        }
+        while (size > m_dtr.comp_node.get_max_block_size_available()) {
+            bool evict_suc = auto_evict(1);
+            if (!evict_suc) return false;
+        }
+        return true;
+    };
+    auto pre_level = set_log_level(LogLevel::NO_LOG);
+    reserve_size(x->blob()->size());
+    MGB_TRY { BlobManager::inst()->alloc_direct(x->blob().get(), x->blob()->size()); }
+    MGB_CATCH(MemAllocError&, {
+        bool suc = false;
+        while (!suc) {
+            if (!auto_evict(1)) {
+                break;
+            }
+            MGB_TRY { BlobManager::inst()->alloc_direct(x->blob().get(), x->blob()->size()); }
+            MGB_CATCH(MemAllocError&, { continue; });
+            suc = true;
+        }
+        if (!suc) {
+            set_log_level(pre_level);
+            mgb_log_warn("reallocating all cuda memory to alleviate fragmentation, the performance may be affected");
+            set_log_level(LogLevel::NO_LOG);
+            BlobManager::inst()->defrag(x->blob()->comp_node());
+            BlobManager::inst()->alloc_direct(x->blob().get(), x->blob()->size());
+        }
+    });
+    set_log_level(pre_level);
+}
+
 std::tuple<SmallVector<MemoryDesc>, SmallVector<TensorPtr>, SmallVector<TensorPtr>> ChannelImpl::init_output_and_workspace(
         const OpDef& def,
         SmallVector<TensorPtr> inputs,
@@ -876,11 +908,15 @@ std::tuple<SmallVector<MemoryDesc>, SmallVector<TensorPtr>, SmallVector<TensorPt
             desc.id->id = ++ m_storage_id;
         }
     }
+    auto& state = get_worker_state();
     auto alloc_storage = [&](SmallVector<MemoryDesc>& desc) {
         SmallVector<TensorPtr> tensors;
         for (size_t i = 0; i < desc.size(); i ++) {
             if (desc[i].id->is_sys_alloc()) {
                 tensors.push_back(Tensor::make(desc[i].layout, desc[i].cn));
+                if (!desc[i].layout.is_empty() && state.options.enable_dtr_auto_drop) {
+                    alloc_tensor_with_evict(tensors.back());
+                }
             } else if (desc[i].id->is_from_other()) {
                 for (size_t j = 0; j < inputs_mem_desc.size();j ++) {
                     if (inputs_mem_desc[j].id->desc == desc[i].id->desc) {

imperative/src/impl/interpreter/interpreter_impl.h

@@ -403,19 +403,19 @@ private:
         //! store all tensors that may be evicted
         std::unordered_set<TensorInfo*> candidates;
 
-        //! whether the warning message has been printed
-        bool warn_printed = false;
-
         bool is_bad_op(std::string op_name) {
             return std::find(op_blacklist.begin(), op_blacklist.end(), op_name) != op_blacklist.end();
         }
 
         std::vector<std::string> op_blacklist = {"CollectiveComm", "InplaceAdd",
-                                "ParamPackSplit", "ParamPackConcat", "GaussianRNG"};
+                                "ParamPackSplit", "ParamPackConcat", "GaussianRNG", "UniformRNG",
+                                "GammaRNG", "PermutationRNG", "PoissonRNG", "BetaRNG"};
     } m_dtr;
 
     //! automatically evict an optimal tensor
-    void auto_evict();
+    bool auto_evict(size_t);
+
+    void alloc_tensor_with_evict(TensorPtr);
 
     // assert thread id when call get_xxx_state to avoid misuse
     ChannelState& get_channel_state();

imperative/src/include/megbrain/imperative/blob_manager.h

@@ -22,6 +22,8 @@ public:
 
     static BlobManager* inst();
 
+    virtual void alloc_direct(Blob* blob, size_t size) = 0;
+
     virtual void alloc_with_defrag(Blob* blob, size_t size) = 0;
 
     virtual DeviceTensorND alloc_workspace_with_defrag(CompNode cn, TensorLayout layout) = 0;

src/core/impl/comp_node/cuda/comp_node.cpp

@@ -267,10 +267,14 @@ public:
     }
 
 #if !MGB_BUILD_SLIM_SERVING
-    std::pair<size_t, size_t> get_free_left_and_right(size_t begin_ptr,
-                                                      size_t end_ptr) override {
+    std::pair<size_t, size_t> get_free_left_and_right(size_t begin_ptr, size_t end_ptr) override {
         return m_mem_alloc->get_free_left_and_right(begin_ptr, end_ptr);
     }
+
+    size_t get_max_block_size_available() {
+        activate();
+        return m_mem_alloc->get_max_block_size_available();
+    }
 #endif
 
     Locator locator() override { return m_locator; }

src/core/impl/comp_node/mem_alloc/impl.cpp

@@ -40,6 +40,19 @@ std::pair<size_t, size_t> MemAllocImplHelper::get_free_left_and_right(size_t beg
     }
     return {left_free, right_free};
 }
+
+size_t MemAllocImplHelper::get_max_block_size_available_unsafe() {
+    if (!m_free_blk_size.size()) {
+        return 0;
+    } else {
+        return m_free_blk_size.rbegin()->first.size;
+    }
+}
+
+size_t MemAllocImplHelper::get_max_block_size_available() {
+    MGB_LOCK_GUARD(m_mutex);
+    return get_max_block_size_available_unsafe();
+}
 #endif
 
 MemAllocImplHelper::MemAddr MemAllocImplHelper::do_alloc(

src/core/impl/comp_node/mem_alloc/impl.h

@@ -116,6 +116,8 @@ class MemAllocImplHelper: virtual public MemAllocBase {
         FreeMemStat get_free_memory_self_unsafe();
 
 #if !MGB_BUILD_SLIM_SERVING
+        size_t get_max_block_size_available_unsafe();
+
         std::pair<size_t, size_t> get_free_left_and_right(size_t begin_ptr, size_t end_ptr) override;
 #endif
 
@@ -123,6 +125,11 @@ class MemAllocImplHelper: virtual public MemAllocBase {
         void print_memory_state() override;
 
         FreeMemStat get_free_memory() override final;
+
+#if !MGB_BUILD_SLIM_SERVING
+        size_t get_max_block_size_available() override final;
+#endif
+
 };
 
 

src/core/include/megbrain/comp_node.h

@@ -359,6 +359,10 @@ class CompNode {
         size_t get_used_memory() const {
             return m_impl->get_used_memory();
         }
+
+        size_t get_max_block_size_available() const {
+            return m_impl->get_max_block_size_available();
+        }
 #endif
 
         //! change to another stream on the same memory node
@@ -545,6 +549,9 @@ class CompNode {
                 virtual size_t get_used_memory() {
                     return 0;
                 }
+                virtual size_t get_max_block_size_available() {
+                    return 0;
+                }
 #endif
 
                 virtual Locator locator() = 0;

src/core/include/megbrain/comp_node/alloc.h

@@ -141,6 +141,10 @@ class MemAllocBase {
         virtual std::pair<size_t, size_t> get_free_left_and_right(size_t begin_ptr, size_t end_ptr) {
             return {0, 0};
         }
+        
+        virtual size_t get_max_block_size_available() {
+            return 0;
+        }
 #endif
 
         virtual ~MemAllocBase() = default;