[Feature] Radix Tree in C++ (#7369)

python/sglang/srt/managers/scheduler.py

@@ -569,7 +569,23 @@ class Scheduler(
                 page_size=self.page_size,
             )
         else:
-            if self.enable_hierarchical_cache:
+            if os.environ.get("SGLANG_EXPERIMENTAL_CPP_RADIX_TREE") == "1":
+                # lazy import to avoid JIT overhead
+                from sglang.srt.mem_cache.radix_cache_cpp import RadixCacheCpp
+
+                self.tree_cache = RadixCacheCpp(
+                    disable=False,
+                    use_hicache=self.enable_hierarchical_cache,
+                    req_to_token_pool=self.req_to_token_pool,
+                    token_to_kv_pool=self.token_to_kv_pool_allocator,
+                    tp_cache_group=self.tp_cpu_group,
+                    page_size=self.page_size,
+                    hicache_ratio=server_args.hicache_ratio,
+                    hicache_size=server_args.hicache_size,
+                    hicache_write_policy=server_args.hicache_write_policy,
+                    enable_kv_cache_events=self.enable_kv_cache_events,
+                )
+            elif self.enable_hierarchical_cache:
                 self.tree_cache = HiRadixCache(
                     req_to_token_pool=self.req_to_token_pool,
                     token_to_kv_pool_allocator=self.token_to_kv_pool_allocator,

python/sglang/srt/mem_cache/cpp_radix_tree/.clang-format

@@ -0,0 +1 @@
+../../../../../sgl-kernel/.clang-format

python/sglang/srt/mem_cache/cpp_radix_tree/common.h

@@ -0,0 +1,29 @@
+#pragma once
+#include <cstddef>
+#include <cstdint>
+#include <source_location>
+#include <span>
+#include <stdexcept>
+#include <string>
+#include <vector>
+
+namespace radix_tree_v2 {
+
+using token_t = std::int32_t;
+using token_vec_t = std::vector<token_t>;
+using token_slice = std::span<const token_t>;
+using NodeHandle = std::size_t;
+using IOTicket = std::uint32_t;
+
+inline void _assert(
+    bool condition,
+    const char* message = "Assertion failed",
+    std::source_location loc = std::source_location::current()) {
+  if (!condition) [[unlikely]] {
+    std::string msg = message;
+    msg = msg + " at " + loc.file_name() + ":" + std::to_string(loc.line()) + " in " + loc.function_name();
+    throw std::runtime_error(msg);
+  }
+}
+
+}  // namespace radix_tree_v2

python/sglang/srt/mem_cache/cpp_radix_tree/radix_tree.py

@@ -0,0 +1,182 @@
+from __future__ import annotations
+
+import os
+from typing import TYPE_CHECKING, List, Optional, Tuple
+
+import torch
+from torch.utils.cpp_extension import load
+
+_abs_path = os.path.dirname(os.path.abspath(__file__))
+radix_tree_cpp = load(
+    name="radix_tree_cpp",
+    sources=[
+        f"{_abs_path}/tree_v2_binding.cpp",
+        f"{_abs_path}/tree_v2_debug.cpp",
+        f"{_abs_path}/tree_v2.cpp",
+    ],
+    extra_cflags=["-O3", "-std=c++20"],
+)
+
+if TYPE_CHECKING:
+
+    class TreeNodeCpp:
+        """
+        A placeholder for the TreeNode class. Cannot be constructed elsewhere.
+        """
+
+    class IOHandle:
+        """
+        A placeholder for the IOHandle class. Cannot be constructed elsewhere.
+        """
+
+    class RadixTreeCpp:
+        def __init__(
+            self,
+            disabled: bool,
+            host_size: Optional[int],
+            page_size: int,
+            write_through_threshold: int,
+        ):
+            """
+            Initializes the RadixTreeCpp instance.
+            Args:
+                disabled (bool): If True, the radix tree is disabled.
+                host_size (Optional[int]): Size of the radix tree on the CPU. None means no CPU tree.
+                page_size (int): Size of the page for the radix tree.
+                write_through_threshold (int): Threshold for writing through from GPU to CPU.
+            """
+            self.tree = radix_tree_cpp.RadixTree(  # type: ignore
+                disabled, host_size, page_size, write_through_threshold
+            )
+
+        def match_prefix(
+            self, prefix: List[int]
+        ) -> Tuple[List[torch.Tensor], int, TreeNodeCpp, TreeNodeCpp]:
+            """
+            Matches a prefix in the radix tree.
+            Args:
+                prefix (List[int]): The prefix to match.
+            Returns:
+                Tuple[List[torch.Tensor], TreeNodeCpp, TreeNodeCpp]:
+                    0. A list of indices that is matched by the prefix on the GPU.
+                    1. Sum length of the indices matched on the CPU.
+                    2. The last node of the prefix matched on the GPU.
+                    3. The last node of the prefix matched on the CPU.
+            """
+            return self.tree.match_prefix(prefix)
+
+        def evict(self, num_tokens: int) -> List[torch.Tensor]:
+            """
+            Evicts a number of tokens from the radix tree.
+            Args:
+                num_tokens (int): The number of tokens to evict.
+            Returns:
+                List[torch.Tensor]: A list of indices that were evicted.
+            """
+            return self.tree.evict(num_tokens)
+
+        def lock_ref(self, handle: TreeNodeCpp, lock: bool) -> None:
+            """
+            Locks or unlocks a reference to a tree node.
+            After locking, the node will not be evicted from the radix tree.
+            Args:
+                handle (TreeNodeCpp): The tree node to lock or unlock.
+                lock (bool): If True, locks the node; if False, unlocks it.
+            """
+            return self.tree.lock_ref(handle, lock)
+
+        def writing_through(
+            self, key: List[int], indices: torch.Tensor
+        ) -> Tuple[List[Tuple[IOHandle, torch.Tensor, torch.Tensor]], int]:
+            """
+            Inserts a key-value pair into the radix tree and perform write-through check.
+            Args:
+                key (List[int]): The key to insert.
+                indices (torch.Tensor): The value associated with the key.
+            Returns:
+                Tuple[List[Tuple[IOHandle, torch.Tensor, torch.Tensor]], int]:
+                    0. A list of (IOHandle, device indices, host indices) tuples.
+                       These IOhandles require write-through to the CPU in python side.
+                    1. The number of indices that are matched on device.
+            """
+            return self.tree.writing_through(key, indices)
+
+        def loading_onboard(
+            self,
+            host_node: TreeNodeCpp,
+            new_device_indices: torch.Tensor,
+        ) -> Tuple[IOHandle, List[torch.Tensor]]:
+            """
+            Updates the device indices of tree nodes within a range on the tree.
+            Args:
+                host_node (TreeNodeCpp): The tree node on the host, must be descendant of device_node.
+                new_device_indices (torch.Tensor): The new device indices to set.
+                    The length of this tensor must be exactly host indices length.
+            Returns:
+                Tuple[IOHandle, List[torch.Tensor]]:
+                    0. An IOHandle that requires loading to the CPU in python side.
+                    1. A list of host indices corresponding to the new device indices.
+            """
+            return self.tree.loading_onboard(host_node, new_device_indices)
+
+        def commit_writing_through(self, handle: IOHandle, success: bool) -> None:
+            """
+            Commits the write-through process for a tree node.
+            Args:
+                handle (IOHandle): The IOHandle to commit.
+                success (bool): If True, commits the write-through; if False, just indicates failure.
+            """
+            return self.tree.commit_writing_through(handle, success)
+
+        def commit_loading_onboard(self, handle: IOHandle, success: bool) -> None:
+            """
+            Commits the load onboard process for tree nodes within a range on the tree.
+            Args:
+                handle (IOHandle): The IOHandle to commit.
+                success (bool): If True, commits the load-onboard; if False, just indicates failure.
+            """
+            return self.tree.commit_loading_onboard(handle, success)
+
+        def evictable_size(self) -> int:
+            """
+            Returns the size of the evictable part of the radix tree.
+            This is the size of the part that can be evicted from the GPU (ref_count = 0).
+            Returns:
+                int: The size of the evictable part.
+            """
+            return self.tree.evictable_size()
+
+        def protected_size(self) -> int:
+            """
+            Returns the size of the protected part of the radix tree.
+            This is the size of the part that cannot be evicted from the GPU (ref_count > 0).
+            Returns:
+                int: The size of the protected part.
+            """
+            return self.tree.protected_size()
+
+        def total_size(self) -> int:
+            """
+            Returns the total size of the radix tree (including CPU nodes).
+            Returns:
+                int: The total size of the radix tree.
+            """
+            return self.tree.total_size()
+
+        def reset(self) -> None:
+            """
+            Resets the radix tree, clearing all nodes and indices.
+            """
+            return self.tree.reset()
+
+        def debug_print(self) -> None:
+            """
+            Prints the internal state of the radix tree for debugging purposes.
+            """
+            return self.tree.debug_print()
+
+else:
+    # Real implementation of the classes for runtime
+    RadixTreeCpp = radix_tree_cpp.RadixTree
+    TreeNodeCpp = object
+    IOHandle = object

python/sglang/srt/mem_cache/cpp_radix_tree/tree_v2.cpp

@@ -0,0 +1,143 @@
+#include "tree_v2.h"
+
+#include <ATen/core/TensorBody.h>
+#include <ATen/ops/empty.h>
+#include <ATen/ops/tensor.h>
+#include <ATen/ops/zeros.h>
+#include <c10/util/irange.h>
+
+#include <cstddef>
+#include <memory>
+#include <queue>
+#include <stdexcept>
+#include <utility>
+#include <vector>
+
+#include "common.h"
+#include "tree_v2_impl.h"
+#include "tree_v2_node.h"
+
+namespace radix_tree_v2 {
+
+static NodeHandle node2id(TreeNode* node) {
+  return node->node_id;
+}
+
+// compare function for the TreeNode pointers based on their time
+// we use LRU, so we want to evict the least recently used nodes
+// since std::priority_queue is a max-heap, we need to reverse the comparison
+static constexpr auto cmp = [](TreeNode* lhs, TreeNode* rhs) { return lhs->time() > rhs->time(); };
+
+RadixTree::RadixTree(bool disabled, std::optional<std::size_t> host_size, std::size_t page_size, std::size_t threshold)
+    : m_impl(std::make_unique<Impl>(disabled, host_size.has_value(), page_size, host_size.value_or(0), threshold)) {}
+
+RadixTree::~RadixTree() = default;
+
+std::tuple<std::vector<at::Tensor>, std::size_t, NodeHandle, NodeHandle>
+RadixTree::match_prefix(const token_vec_t& _key) {
+  if (m_impl->disabled) return {};
+
+  const auto key = token_slice{_key.data(), m_impl->align(_key.size())};
+  const auto [host_node, _] = m_impl->tree_walk(key);
+
+  // walk up to the first non-evicted node
+  std::size_t host_hit_length = 0;
+  const auto device_node = host_node;
+
+  // collect all the device indices
+  std::vector<at::Tensor> indices{};
+  walk_to_root(device_node, [&](TreeNode* n) { indices.push_back(n->device_indices()); });
+  std::reverse(indices.begin(), indices.end());
+
+  return {std::move(indices), host_hit_length, node2id(device_node), node2id(host_node)};
+}
+
+std::vector<at::Tensor> RadixTree::evict(std::size_t num_tokens) {
+  if (m_impl->disabled || num_tokens == 0) return {};
+  auto heap = std::priority_queue{cmp, m_impl->collect_leaves_device()};
+  std::vector<at::Tensor> evicted_values;
+  // evict nodes until we reach the desired number of tokens
+  std::size_t num_evict = 0;
+  while (num_evict < num_tokens && !heap.empty()) {
+    const auto node = heap.top();
+    heap.pop();
+    // when ref_count == 0, can't be writing through
+    _assert(node->on_gpu() && node->ref_count == 0);
+    if (!node->is_io_free()) continue;  // skip nodes that are undergoing IO (i.e. indices protected)
+    evicted_values.push_back(node->device_indices());
+    num_evict += node->length();
+    const auto parent = node->parent();
+    m_impl->remove_device_node(node);
+    if (parent->is_leaf_device() && parent->ref_count == 0)
+      heap.push(parent);  // push parent to the heap if it is now a free leaf
+  }
+
+  return evicted_values;
+}
+
+std::tuple<std::vector<std::tuple<IOTicket, at::Tensor, at::Tensor>>, std::size_t>
+RadixTree::writing_through(const token_vec_t& _key, at::Tensor value) {
+  if (m_impl->disabled) return {};
+  _assert(_key.size() == std::size_t(value.size(0)), "Key and value must have the same size");
+
+  // just align the key to the page size, clip the unaligned tail
+  const auto key = token_slice{_key.data(), m_impl->align(_key.size())};
+
+  // walk the tree to find the right place to insert
+  const auto [host_node, host_prefix_length] = m_impl->tree_walk(key);
+
+  // insert and create a new node if the remaining part of the key is not empty
+  if (host_prefix_length != key.size()) {
+    m_impl->create_device_node(
+        host_node,
+        {key.begin() + host_prefix_length, key.end()},
+        value.slice(/*dim=*/0, host_prefix_length, key.size()));
+  }
+
+  // add the hit count for the device node
+  walk_to_root(host_node, [&](TreeNode* n) { n->hit_count++; });
+
+  std::vector<std::tuple<IOTicket, at::Tensor, at::Tensor>> result;
+
+  // don't write through if hicache is disabled (no host memory), fast path
+  if (!m_impl->use_hicache) return {std::move(result), host_prefix_length};
+  throw std::runtime_error("Not implemented yet");
+}
+
+std::tuple<IOTicket, std::vector<at::Tensor>> RadixTree::loading_onboard(NodeHandle, at::Tensor) {
+  if (m_impl->disabled) return {};
+  throw std::runtime_error("Not implemented yet");
+}
+
+void RadixTree::commit_writing_through(IOTicket, bool) {
+  if (m_impl->disabled) return;
+  throw std::runtime_error("Not implemented yet");
+}
+
+void RadixTree::commit_loading_onboard(IOTicket, bool) {
+  if (m_impl->disabled) return;
+  throw std::runtime_error("Not implemented yet");
+}
+
+void RadixTree::reset() {
+  m_impl->reset();
+}
+
+void RadixTree::lock_ref(NodeHandle node_id, bool increment) {
+  if (m_impl->disabled) return;
+  m_impl->lock_ref(node_id, increment);
+}
+
+std::size_t RadixTree::evictable_size() const {
+  return m_impl->evictable_size();
+}
+
+std::size_t RadixTree::protected_size() const {
+  return m_impl->protected_size();
+}
+
+std::size_t RadixTree::total_size() const {
+  return m_impl->total_size();
+}
+
+}  // namespace radix_tree_v2

python/sglang/srt/mem_cache/cpp_radix_tree/tree_v2.h

@@ -0,0 +1,59 @@
+#pragma once
+#include <ATen/core/TensorBody.h>
+#include <c10/core/Device.h>
+
+#include <cstddef>
+#include <memory>
+#include <optional>
+#include <tuple>
+#include <vector>
+
+#include "common.h"
+
+namespace radix_tree_v2 {
+
+struct RadixTree {
+ public:
+  RadixTree(bool disabled, std::optional<std::size_t> host_size, std::size_t page_size, std::size_t threshold);
+  ~RadixTree();
+
+  // Trees should not be copied or moved, as they manage their own memory and state.
+  RadixTree(const RadixTree&) = delete;
+  RadixTree(RadixTree&&) = delete;
+  RadixTree& operator=(const RadixTree&) = delete;
+  RadixTree& operator=(RadixTree&&) = delete;
+
+  /// @return (device indices that are matched, host indices length, device node, host node)
+  std::tuple<std::vector<at::Tensor>, std::size_t, NodeHandle, NodeHandle> match_prefix(const token_vec_t& key);
+  /// @return Device indices that need to be evicted (on python side).
+  std::vector<at::Tensor> evict(std::size_t num_tokens);
+  /// @brief (Un-)Lock a node.
+  void lock_ref(NodeHandle node_id, bool increment /* increment or decrement */);
+  /// @brief Update new key-value pair and try to perform write-through.
+  std::tuple<std::vector<std::tuple<IOTicket, at::Tensor, at::Tensor>>, std::size_t>
+  writing_through(const token_vec_t& key, at::Tensor value);
+  /// @brief Load to device from host within a range of nodes.
+  std::tuple<IOTicket, std::vector<at::Tensor>> loading_onboard(NodeHandle host_id, at::Tensor indices);
+  /// @brief Commit a transaction of write-through.
+  void commit_writing_through(IOTicket ticket, bool success);
+  /// @brief Commit a transaction of load onboard.
+  void commit_loading_onboard(IOTicket ticket, bool success);
+  /// @brief Clear and reset the tree.
+  void reset();
+
+  /// @return How many size are still evictable (on device + not locked).
+  std::size_t evictable_size() const;
+  /// @return How many size are protected (locked).
+  std::size_t protected_size() const;
+  /// @return How many size are used on device.
+  std::size_t total_size() const;
+
+  /// @brief Print debug information of the tree.
+  void debug_print() const;
+
+ private:
+  struct Impl;
+  std::unique_ptr<Impl> m_impl;
+};
+
+}  // namespace radix_tree_v2

python/sglang/srt/mem_cache/cpp_radix_tree/tree_v2_binding.cpp

@@ -0,0 +1,32 @@
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+#include <torch/extension.h>
+
+#include <cstddef>
+#include <optional>
+
+#include "tree_v2.h"
+
+PYBIND11_MODULE(radix_tree_cpp, m) {
+  using namespace radix_tree_v2;
+  namespace py = pybind11;
+  py::class_<RadixTree>(m, "RadixTree")
+      .def(
+          py::init<bool, std::optional<std::size_t>, std::size_t, std::size_t>(),
+          py::arg("disabled"),
+          py::arg("host_size"),
+          py::arg("page_size"),
+          py::arg("write_through_threshold"))
+      .def("match_prefix", &RadixTree::match_prefix)
+      .def("evict", &RadixTree::evict)
+      .def("lock_ref", &RadixTree::lock_ref)
+      .def("evictable_size", &RadixTree::evictable_size)
+      .def("protected_size", &RadixTree::protected_size)
+      .def("total_size", &RadixTree::total_size)
+      .def("writing_through", &RadixTree::writing_through)
+      .def("loading_onboard", &RadixTree::loading_onboard)
+      .def("commit_writing_through", &RadixTree::commit_writing_through)
+      .def("commit_loading_onboard", &RadixTree::commit_loading_onboard)
+      .def("reset", &RadixTree::reset)
+      .def("debug_print", &RadixTree::debug_print);
+}

python/sglang/srt/mem_cache/cpp_radix_tree/tree_v2_debug.cpp

@@ -0,0 +1,194 @@
+#include <c10/core/DeviceType.h>
+#include <c10/core/MemoryFormat.h>
+#include <c10/core/ScalarType.h>
+
+#include <cstddef>
+#include <cstdlib>
+#include <iostream>
+#include <stdexcept>
+#include <string>
+
+#include "tree_v2.h"
+#include "tree_v2_impl.h"
+
+namespace radix_tree_v2 {
+
+void RadixTree::debug_print() const {
+  m_impl->debug_print(std::clog);
+}
+
+static constexpr auto npos = std::size_t(-1);
+
+void RadixTree::Impl::debug_print(std::ostream& os) const {
+  static constexpr auto _check = [](bool condition, auto msg, std::size_t id = npos) {
+    if (!condition) {
+      std::string suffix = id == npos ? "" : " [id = " + std::to_string(id) + "]";
+      throw std::runtime_error(std::string("RadixTree::debug_print failed: ") + msg + suffix);
+    }
+  };
+
+  static constexpr auto _print_node = [](TreeNode* node, std::size_t depth, std::ostream& os) {
+    const auto length = node->length();
+    os << node->node_id << " [depth = " << depth << "] [len = " << length << "]";
+
+    // placement status
+    if (node->on_both()) {
+      os << " [cpu + gpu]";
+    } else if (node->on_gpu()) {
+      os << " [gpu]";
+    } else if (node->on_cpu()) {
+      os << " [cpu]";
+    } else {
+      _check(false, "Node is not on GPU or CPU", node->node_id);
+    }
+
+    // IO status
+    if (node->is_io_free()) {
+      os << " [io = free]";
+    } else if (node->is_io_device_to_host()) {
+      os << " [io = gpu -> cpu]";
+    } else if (node->is_io_host_to_device()) {
+      os << " [io = cpu -> gpu]";
+    } else {
+      _check(false, "Node is in unknown IO state", node->node_id);
+    }
+
+    os << " [rc = " << node->ref_count << "]";
+    os << " [hit = " << node->hit_count << "]";
+  };
+
+  static constexpr auto _print_indices = [](at::Tensor indices, std::ostream& os) {
+    if (!indices.defined()) {
+      os << "[[N/A]]";
+      return indices;
+    }
+    indices = indices.to(c10::kCPU, c10::kLong, false, false, c10::MemoryFormat::Contiguous);
+    const auto length = indices.numel();
+    os << "[";
+    auto* data_ptr = indices.data_ptr<int64_t>();
+    for (const auto i : c10::irange(indices.size(0))) {
+      os << data_ptr[i];
+      if (i != length - 1) os << ", ";
+    }
+    os << "]";
+    return indices;
+  };
+
+  os << "Evictable size: " << evictable_size() << std::endl;
+  os << "Protected size: " << protected_size() << std::endl;
+  os << "Total size: " << const_cast<Impl*>(this)->total_size() << std::endl;
+  std::vector<std::tuple<TreeNode*, TreeNode*, token_slice>> stack;
+  auto root = const_cast<TreeNode*>(&m_root);
+  os << root->node_id << " [root]" << std::endl;
+  for (const auto& [key, child] : *root) {
+    stack.push_back({child.get(), root, key});
+  }
+
+  std::unordered_map<TreeNode*, std::size_t> depth_map;
+  std::string indent_buffer;
+  depth_map[root] = 0;
+  std::vector<NodeHandle> visited_id;
+  std::size_t evictable_size_real = 0;
+  while (!stack.empty()) {
+    const auto [node, parent, key] = stack.back();
+    stack.pop_back();
+    visited_id.push_back(node->node_id);
+    const auto nid = node->node_id;
+    _check(node != nullptr, "Node is null", nid);
+    _check(node->on_gpu() || node->on_cpu(), "Node is not on GPU or CPU", nid);
+    _check(node->parent() == parent, "Parent is not correct", nid);
+    _check(key.size() == page_size && node->diff_key(key, 0) == page_size, "Key is not correct", nid);
+    _check(depth_map.count(node) == 0, "Node is visited twice", nid);
+    _check(m_node_map.count(nid) == 1, "Node is not in the map", nid);
+    _check(m_node_map.at(nid) == node, "Node in the map is not the same as the one in the stack", nid);
+    _check(!node->on_gpu() || parent->is_root() || parent->on_gpu(), "Node on GPU must have a GPU/root parent", nid);
+    if (!node->is_io_free()) {
+      _check(node->ref_count > 0, "Node is in IO state but not protected", nid);
+      _check(node->on_both(), "Node in IO state must be on both CPU and GPU", nid);
+    }
+
+    if (node->on_gpu() && node->ref_count == 0) {
+      evictable_size_real += node->length();
+    }
+
+    const auto depth = (depth_map[node] = depth_map[parent] + 1);
+    indent_buffer.resize(depth * 2, ' ');
+    os << indent_buffer;
+    _print_node(node, depth, os);
+    os << std::endl;
+    for (const auto& [key, child] : *node) {
+      stack.push_back({child.get(), node, key});
+    }
+  }
+
+  _check(evictable_size_real == evictable_size(), "Evictable size is wrong");
+  _check(m_node_map.count(root->node_id) == 1, "Root node is not in the map");
+  _check(m_node_map.at(root->node_id) == root, "Root node in the map is not correct");
+
+  std::sort(visited_id.begin(), visited_id.end());
+  if (visited_id.size() != m_node_map.size() - 1) {
+    // Some error in the tree, not all nodes are visited
+    std::string id_list;
+    id_list += "(visited: ";
+    id_list += std::to_string(root->node_id) + " ";
+    for (const auto& id : visited_id) {
+      id_list += std::to_string(id) + " ";
+    }
+    id_list += "), (in map: ";
+    for (const auto& [id, _] : m_node_map) {
+      id_list += std::to_string(id) + " ";
+    }
+    id_list += ")";
+    _check(false, "Not all nodes are visited " + id_list);
+  }
+
+  static const auto kSGLANG_RADIX_CPP_DEBUG_LIMIT = [] {
+    const char* env = std::getenv("SGLANG_RADIX_CPP_DEBUG_LIMIT");
+    const std::size_t default_limit = 16;
+    if (env != nullptr) {
+      try {
+        return static_cast<std::size_t>(std::stoull(env));
+      } catch (const std::exception& e) {
+        std::cerr << "Invalid SGLANG_RADIX_CPP_DEBUG_LIMIT value: " << env  //
+                  << ". Using default value =" << default_limit << std::endl;
+      }
+    }
+    return default_limit;
+  }();
+
+  for (const auto nid : visited_id) {
+    const auto node = m_node_map.at(nid);
+    // print key and indices
+    const auto& key = node->_unsafe_tokens();
+    if (key.size() > kSGLANG_RADIX_CPP_DEBUG_LIMIT) {
+      os << "Node " << nid << ": key is too long (" << key.size() << " tokens), skipping..." << std::endl;
+      continue;
+    }
+    os << "Node " << nid << ": key = [";
+    for (const auto& i : c10::irange(key.size())) {
+      os << key[i];
+      if (i != key.size() - 1) os << ", ";
+    }
+
+    _check(key.size() % page_size == 0, "Misaligned key", nid);
+
+    os << "] device_indices = ";
+    const auto device_indices = _print_indices(node->device_indices(), os);
+    if (device_indices.defined()) {
+      std::size_t length = device_indices.numel();
+      _check(device_indices.dim() == 1, "Device indices must be 1D tensor", nid);
+      _check(length == node->length(), "Wrong device indices size", nid);
+    }
+
+    os << " host_indices = ";
+    const auto host_indices = _print_indices(node->host_indices(), os);
+    if (host_indices.defined()) {
+      std::size_t length = host_indices.numel();
+      _check(host_indices.dim() == 1, "Host indices must be 1D tensor", nid);
+      _check(length == node->length(), "Wrong host indices size", nid);
+    }
+    os << std::endl;
+  }
+}
+
+}  // namespace radix_tree_v2

python/sglang/srt/mem_cache/cpp_radix_tree/tree_v2_impl.h

@@ -0,0 +1,276 @@
+#pragma once
+#include <c10/util/irange.h>
+
+#include <chrono>
+#include <cstddef>
+#include <iosfwd>
+#include <memory>
+#include <unordered_map>
+#include <utility>
+#include <vector>
+
+#include "common.h"
+#include "tree_v2.h"
+#include "tree_v2_node.h"
+
+namespace radix_tree_v2 {
+
+using node_iterator_t = typename TreeNode::iterator_t;
+
+struct RadixTree::Impl {
+ public:
+  Impl(bool disabled, bool use_hicache, std::size_t page_size, std::size_t host_size, std::size_t threshold)
+      : m_root(/*node_id_=*/0),
+        m_evictable_size(0),
+        m_protected_size(0),
+        m_cached_vec(),
+        m_node_map(),
+        m_node_counter(1),  // start from 1 to avoid confusion with root node
+        disabled(disabled),
+        use_hicache(use_hicache),
+        page_size(page_size),
+        threshold(threshold) {
+    _assert(page_size > 0, "Page size must be greater than zero");
+    _assert(use_hicache == (host_size > 0), "Hierarchical cache is enabled iff host size > 0");
+    m_root.ref_count = 1;                  // root node is always protected
+    m_cached_vec.reserve(page_size);       // to avoid repeated allocations
+    m_node_map[m_root.node_id] = &m_root;  // add root to the map
+  }
+
+  TreeNode* split_node(node_iterator_t iterator, std::size_t prefix_length) {
+    // from `parent -> old_node` to `parent-> new_node -> old_node`
+    // the prefix part of the old node is moved to the new node
+    auto old_node_ptr = std::move(iterator->second);
+    auto new_node_ptr = std::make_unique<TreeNode>(m_node_counter++);
+    auto* old_node = old_node_ptr.get();
+    auto* new_node = new_node_ptr.get();
+    auto* parent = old_node->parent();
+    // set up data structures
+    split_prefix(new_node, old_node, prefix_length);
+    // set up parent-child relationship
+    add_child(new_node, std::move(old_node_ptr));
+    add_child(parent, std::move(new_node_ptr), iterator);
+    m_node_map[new_node->node_id] = new_node;  // add to the map
+    return new_node;
+  }
+
+  // node: x -> [GPU]
+  TreeNode* create_device_node(TreeNode* parent, token_vec_t vec, at::Tensor indices) {
+    auto new_node_ptr = std::make_unique<TreeNode>(m_node_counter++);
+    auto new_node = new_node_ptr.get();
+    new_node_ptr->_unsafe_tokens() = std::move(vec);
+    new_node_ptr->_unsafe_device_indices() = std::move(indices);
+    m_evictable_size += new_node_ptr->length();
+    add_child(parent, std::move(new_node_ptr));
+    m_node_map[new_node->node_id] = new_node;  // add to the map
+    return new_node;
+  }
+
+  // node: [GPU] -> x
+  void remove_device_node(TreeNode* node) {
+    _assert(node->on_gpu_only() && node->ref_count == 0);
+    m_evictable_size -= node->length();
+    node->parent()->erase_child(get_key(node));
+    m_node_map.erase(node->node_id);  // remove from the map
+  }
+
+  /**
+   * @brief Walk the tree to find the node that matches the key.
+   * If the key partially matches a node, it will split that node.
+   * @return A pair containing the last node that matches the key and
+   * the total prefix length matched (on gpu and cpu) so far.
+   */
+  std::pair<TreeNode*, std::size_t> tree_walk(token_slice key) {
+    _assert(key.size() % page_size == 0, "Key should be page-aligned");
+
+    std::size_t total_prefix_length = 0;
+    TreeNode* node = &m_root;
+
+    const auto now = std::chrono::steady_clock::now();
+    while (key.size() > 0) {
+      const auto iterator = node->find_child(get_key(key));
+      if (iterator == node->end()) break;
+
+      // walk to the child node
+      node = iterator->second.get();
+
+      // at least `page_size` tokens are matched, and there may be more tokens to match
+      // the return value prefix_length is no less than `page_size`
+      const auto prefix_length = align(node->diff_key(key, page_size) + page_size);
+      total_prefix_length += prefix_length;
+
+      // split the node if the prefix is not the whole token vector
+      if (prefix_length < node->length()) {
+        return {split_node(iterator, prefix_length), total_prefix_length};
+      }
+
+      // we have matched the whole key, continue to the next node
+      node->access(now);
+      key = key.subspan(prefix_length);
+    }
+
+    return {node, total_prefix_length};
+  }
+
+  std::vector<TreeNode*> collect_leaves() const {
+    std::vector<TreeNode*> leaves;
+    std::vector<TreeNode*> stack = {};
+    for (const auto& [_, child] : m_root) {
+      stack.push_back(child.get());
+    }
+    while (!stack.empty()) {
+      const auto node = stack.back();
+      stack.pop_back();
+      if (node->is_leaf()) {
+        if (node->ref_count == 0) {
+          leaves.push_back(node);
+        }
+      } else {
+        for (const auto& [_, child] : *node) {
+          stack.push_back(child.get());
+        }
+      }
+    }
+    return leaves;
+  }
+
+  std::vector<TreeNode*> collect_leaves_device() const {
+    // for non-hicache, every leaf device node is a leaf node (since no backup on host)
+    if (!use_hicache) return collect_leaves();
+    std::vector<TreeNode*> leaves;
+    std::vector<TreeNode*> stack = {};
+    for (const auto& [_, child] : m_root) {
+      stack.push_back(child.get());
+    }
+    while (!stack.empty()) {
+      const auto node = stack.back();
+      stack.pop_back();
+      if (!node->on_gpu()) continue;  // skip nodes that are not on GPU
+      if (node->is_leaf_device()) {
+        if (node->ref_count == 0) {
+          leaves.push_back(node);
+        }
+      } else {
+        for (const auto& [_, child] : *node) {
+          stack.push_back(child.get());
+        }
+      }
+    }
+    return leaves;
+  }
+
+  void lock_ref(TreeNode* node, bool increment) {
+    if (node->is_root()) return;  // skip root node
+    _assert(node->on_gpu(), "Cannot lock reference on an evicted node");
+    if (increment)
+      walk_to_root(node, [this](TreeNode* n) {
+        if (n->ref_count == 0) {
+          m_evictable_size -= n->length();
+          m_protected_size += n->length();
+        }
+        n->ref_count++;
+      });
+    else
+      walk_to_root(node, [this](TreeNode* n) {
+        _assert(n->ref_count != 0, "Cannot decrement reference count = zero");
+        n->ref_count--;
+        if (n->ref_count == 0) {
+          m_protected_size -= n->length();
+          m_evictable_size += n->length();
+        }
+      });
+  }
+
+  void lock_ref(NodeHandle node_ptr, bool increment) {
+    return lock_ref(id2node(node_ptr), increment);
+  }
+
+  void lock(TreeNode* node) {
+    return lock_ref(node, /*increment=*/true);
+  }
+
+  void unlock(TreeNode* node) {
+    return lock_ref(node, /*increment=*/false);
+  }
+
+  std::size_t total_size() const {
+    std::size_t size = 0;
+    std::vector<const TreeNode*> stack = {&m_root};
+    while (!stack.empty()) {
+      auto* node = stack.back();
+      stack.pop_back();
+      size += node->length();
+      for (const auto& [_, child] : *node)
+        stack.push_back(child.get());
+    }
+    return size;
+  }
+
+  std::size_t evictable_size() const {
+    return m_evictable_size;
+  }
+
+  std::size_t protected_size() const {
+    return m_protected_size;
+  }
+
+  std::size_t align(std::size_t size) const {
+    return (size / page_size) * page_size;  // align to page size
+  }
+
+  TreeNode* id2node(NodeHandle node_id) const {
+    const auto iterator = m_node_map.find(node_id);
+    _assert(iterator != m_node_map.end(), "Node not found in the map");
+    return iterator->second;
+  }
+
+  void reset() {
+    _assert(m_root.ref_count == 1, "Root node must be protected during reset");
+    m_node_counter = 1;  // reset node counter
+    m_root.root_reset();
+    m_evictable_size = 0;
+    m_protected_size = 0;
+    m_node_map.clear();
+    m_node_map[m_root.node_id] = &m_root;  // re-add root to the map
+  }
+
+  void debug_print(std::ostream& os) const;
+
+ private:
+  // some auxiliary functions
+  token_vec_t& get_key(token_slice tokens) {
+    _assert(tokens.size() >= page_size, "Key should be at least page-sized");
+    tokens = tokens.subspan(0, page_size);
+    m_cached_vec.assign(tokens.begin(), tokens.end());
+    return m_cached_vec;
+  }
+
+  // justify for _unsafe call: we need to read the key part of the tokens
+  token_vec_t& get_key(TreeNode* node) {
+    return get_key(node->_unsafe_tokens());
+  }
+
+  void add_child(TreeNode* parent, std::unique_ptr<TreeNode>&& child) {
+    parent->add_child(get_key(child.get()), std::move(child));
+  }
+
+  void add_child(TreeNode* parent, std::unique_ptr<TreeNode>&& child, node_iterator_t it) {
+    parent->add_child(it, std::move(child));
+  }
+
+  TreeNode m_root;                                        // root node of the tree
+  std::size_t m_evictable_size;                           // number of evictable tokens on GPU (lock ref = 0)
+  std::size_t m_protected_size;                           // number of protected tokens on GPU (lock ref > 0)
+  token_vec_t m_cached_vec;                               // cached vector of tokens for the current operation
+  std::unordered_map<std::size_t, TreeNode*> m_node_map;  // map of node keys to nodes
+  std::size_t m_node_counter;                             // counter for node IDs
+
+ public:
+  // some public constant configurations (without m_ prefix)
+  const bool disabled;          // whether the cache is enabled, or just a temporary cache
+  const bool use_hicache;       // whether to use the HiCache for this tree
+  const std::size_t page_size;  // size of each page in the cache
+  const std::size_t threshold;  // threshold for write_through
+};
+
+}  // namespace radix_tree_v2

python/sglang/srt/mem_cache/cpp_radix_tree/tree_v2_node.h

@@ -0,0 +1,257 @@
+#pragma once
+#include <ATen/core/TensorBody.h>
+
+#include <algorithm>
+#include <array>
+#include <chrono>
+#include <cstddef>
+#include <cstdint>
+#include <memory>
+#include <optional>
+#include <ranges>
+#include <unordered_map>
+
+#include "common.h"
+
+namespace radix_tree_v2 {
+
+struct std_vector_hash {
+  // see https://stackoverflow.com/questions/20511347/a-good-hash-function-for-a-vector
+  std::size_t operator()(const token_vec_t& vec) const {
+    std::size_t hash = 0;
+    for (const auto& token : vec) {
+      hash ^= token + 0x9e3779b9 + (hash << 6) + (hash >> 2);
+    }
+    return hash;
+  }
+};
+
+struct TreeNode {
+ public:
+  using childern_map_t = std::unordered_map<token_vec_t, std::unique_ptr<TreeNode>, std_vector_hash>;
+  using iterator_t = typename childern_map_t::iterator;
+  using const_iterator_t = typename childern_map_t::const_iterator;
+  using timestamp_t = std::chrono::steady_clock::time_point;
+
+  TreeNode(std::size_t node_id_)
+      : ref_count(0),
+        hit_count(0),
+        m_io_locked(std::nullopt),
+        m_io_status(IOStatus::None),
+        m_io_ticket(),
+        m_tokens(),
+        m_device_indices(),
+        m_host_indices(),
+        m_parent(),
+        m_children(),
+        m_last_access_time(std::chrono::steady_clock::now()),
+        node_id(node_id_) {}
+
+  void access(timestamp_t time = std::chrono::steady_clock::now()) {
+    m_last_access_time = time;
+  }
+
+  bool is_root() const {
+    return m_parent == nullptr;
+  }
+
+  timestamp_t time() const {
+    return m_last_access_time;
+  }
+
+  bool on_gpu() const {
+    return m_device_indices.defined();
+  }
+
+  bool on_cpu() const {
+    return m_host_indices.defined();
+  }
+
+  bool on_gpu_only() const {
+    return on_gpu() && !on_cpu();
+  }
+
+  bool on_cpu_only() const {
+    return !on_gpu() && on_cpu();
+  }
+
+  bool on_both() const {
+    return on_gpu() && on_cpu();
+  }
+
+  std::size_t length() const {
+    return m_tokens.size();
+  }
+
+  bool is_leaf() const {
+    return m_children.empty();
+  }
+
+  bool is_leaf_device() const {
+    for (const auto& [_, child] : m_children)
+      if (child->on_gpu()) return false;  // at least one child is on the device
+    return true;
+  }
+
+  void add_child(const token_vec_t& v, std::unique_ptr<TreeNode>&& child) {
+    child->m_parent = this;
+    m_children[v] = std::move(child);
+  }
+
+  void add_child(iterator_t it, std::unique_ptr<TreeNode>&& child) {
+    child->m_parent = this;
+    it->second = std::move(child);
+  }
+
+  void erase_child(const token_vec_t& v) {
+    _assert(m_children.erase(v) > 0, "Child node not found");
+  }
+
+  iterator_t find_child(const token_vec_t& v) {
+    return m_children.find(v);
+  }
+
+  iterator_t begin() {
+    return m_children.begin();
+  }
+
+  iterator_t end() {
+    return m_children.end();
+  }
+
+  const_iterator_t begin() const {
+    return m_children.begin();
+  }
+
+  const_iterator_t end() const {
+    return m_children.end();
+  }
+
+  TreeNode* parent() {
+    return m_parent;
+  }
+
+  // set up all data structures except for parent-child relationship
+  friend void split_prefix(TreeNode* new_node, TreeNode* old_node, std::size_t prefix_length) {
+    auto tokens = std::move(old_node->m_tokens);
+    _assert(0 < prefix_length && prefix_length < tokens.size(), "Invalid prefix size for split");
+
+    // set up tokens
+    old_node->m_tokens = token_vec_t(tokens.begin() + prefix_length, tokens.end());
+    new_node->m_tokens = std::move(tokens);
+    new_node->m_tokens.resize(prefix_length);
+
+    // set up values
+    const int64_t new_size = new_node->length();
+    const int64_t old_size = old_node->length();
+    if (old_node->m_device_indices.defined()) {
+      auto new_indices = old_node->m_device_indices.split_with_sizes({new_size, old_size});
+      new_node->m_device_indices = std::move(new_indices[0]);
+      old_node->m_device_indices = std::move(new_indices[1]);
+    }
+    if (old_node->m_host_indices.defined()) {
+      auto new_indices = old_node->m_host_indices.split_with_sizes({new_size, old_size});
+      new_node->m_host_indices = std::move(new_indices[0]);
+      old_node->m_host_indices = std::move(new_indices[1]);
+    }
+
+    // set up ref counts and hit counts
+    new_node->ref_count = old_node->ref_count;
+    new_node->hit_count = old_node->hit_count;
+
+    // If the old node (child) was locked for IO, the new node (parent) does not need
+    // to be locked, since it is naturally protected by the child node's lock.
+    if (old_node->m_io_locked.has_value()) {
+      new_node->m_io_locked = false;
+      new_node->m_io_status = old_node->m_io_status;
+      new_node->m_io_ticket = old_node->m_io_ticket;
+    }
+  }
+
+  /// @return The first index in `m_tokens` that differs from `key`.
+  std::size_t diff_key(token_slice key, std::size_t offset) const {
+    const auto a = token_slice{key}.subspan(offset);
+    const auto b = token_slice{m_tokens}.subspan(offset);
+    const auto [it_a, it_b] = std::ranges::mismatch(a, b);
+    return it_a - a.begin();  // return the index of the first differing token
+  }
+
+  at::Tensor device_indices() const {
+    return m_device_indices;
+  }
+  at::Tensor host_indices() const {
+    return m_host_indices;
+  }
+
+  // visiting tokens are always unsafe (use `diff_key` instead)
+  token_vec_t& _unsafe_tokens() {
+    return m_tokens;
+  }
+  at::Tensor& _unsafe_device_indices() {
+    return m_device_indices;
+  }
+  at::Tensor& _unsafe_host_indices() {
+    return m_host_indices;
+  }
+
+  bool is_io_free() const {
+    return m_io_status == IOStatus::None;
+  }
+
+  bool is_io_device_to_host() const {
+    return m_io_status == IOStatus::DeviceToHost;
+  }
+
+  bool is_io_host_to_device() const {
+    return m_io_status == IOStatus::HostToDevice;
+  }
+
+  void root_reset() {
+    _assert(is_root(), "Only root node can call root_reset");
+    _assert(
+        m_io_status == IOStatus::None && m_io_locked == std::nullopt,
+        "IO operation in progress, cannot reset root node");
+    _assert(this->m_tokens.empty(), "Root node tokens should be empty on reset");
+    _assert(
+        !this->m_device_indices.defined() && !this->m_host_indices.defined(),
+        "Root node indices should be always be empty and never assigned");
+    m_children.clear();
+    this->access();
+  }
+
+ public:
+  std::size_t ref_count;
+  std::size_t hit_count;
+
+ private:
+  enum class IOStatus : std::uint8_t {
+    None,
+    HostToDevice,
+    DeviceToHost,
+  };
+
+  std::optional<bool> m_io_locked;  // whether the node is locked in IO operation
+  IOStatus m_io_status;
+  IOTicket m_io_ticket;
+
+  token_vec_t m_tokens;
+  at::Tensor m_device_indices;  // indices of device value
+  at::Tensor m_host_indices;    // indices of host value
+  TreeNode* m_parent;
+  childern_map_t m_children;
+  timestamp_t m_last_access_time;
+
+ public:
+  const std::size_t node_id;  // unique ID for the node
+};
+
+template <typename F>
+inline TreeNode* walk_to_root(TreeNode* t, const F& f) {
+  while (!t->is_root()) {
+    f(t);
+    t = t->parent();
+  }
+  return t;  // return the root node
+}
+
+}  // namespace radix_tree_v2

python/sglang/srt/mem_cache/radix_cache_cpp.py

@@ -0,0 +1,229 @@
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING, List, Set
+
+import torch
+
+from sglang.srt.mem_cache.allocator import BaseTokenToKVPoolAllocator
+from sglang.srt.mem_cache.base_prefix_cache import BasePrefixCache, MatchResult
+from sglang.srt.mem_cache.cpp_radix_tree.radix_tree import (
+    IOHandle,
+    RadixTreeCpp,
+    TreeNodeCpp,
+)
+from sglang.srt.mem_cache.memory_pool import ReqToTokenPool
+
+if TYPE_CHECKING:
+    from sglang.srt.managers.schedule_batch import Req
+
+
+logger = logging.getLogger(__name__)
+
+
+class RadixCacheCpp(BasePrefixCache):
+    def _merge_tensor(self, l: List[torch.Tensor]) -> torch.Tensor:
+        """
+        Merge a list of tensors into a single tensor.
+        Args:
+            l (List[torch.Tensor]): List of tensors to merge.
+        Returns:
+            torch.Tensor: Merged tensor.
+        """
+        if len(l) == 0:
+            return torch.empty(0, dtype=torch.int64, device=self.device)
+        elif len(l) == 1:
+            return l[0]
+        else:
+            return torch.cat(l)
+
+    def __init__(
+        self,
+        disable: bool,
+        use_hicache: bool,
+        req_to_token_pool: ReqToTokenPool,
+        token_to_kv_pool: BaseTokenToKVPoolAllocator,
+        tp_cache_group: torch.distributed.ProcessGroup,
+        page_size: int,
+        hicache_ratio: float,
+        hicache_size: int,
+        hicache_write_policy: str,
+        enable_kv_cache_events: bool = False,
+        hicache_oracle: bool = False,
+        enable_write_cancel: bool = False,
+    ):
+        self.disable = disable
+        self.enable_write_cancel = enable_write_cancel
+
+        assert (
+            enable_kv_cache_events is False
+        ), "HiRadixCache does not support kv cache events yet"
+        self.kv_cache = token_to_kv_pool.get_kvcache()
+
+        # record the nodes with ongoing write through
+        self.ongoing_write_through: Set[IOHandle] = set()
+        # record the node segments with ongoing load back
+        self.ongoing_load_back: Set[IOHandle] = set()
+        # todo: dynamically adjust the threshold
+        self.write_through_threshold = (
+            1 if hicache_write_policy == "write_through" else 2
+        )
+        self.device = token_to_kv_pool.device
+        self.token_to_kv_pool = token_to_kv_pool
+        self.req_to_token_pool = req_to_token_pool
+        self.page_size = page_size
+
+        self.tp_group = tp_cache_group
+
+        if not use_hicache:
+            self.tree = RadixTreeCpp(
+                disabled=self.disable,
+                page_size=page_size,
+                host_size=None,  # no host cache, this should be removed in the future
+                write_through_threshold=self.write_through_threshold,
+            )
+            self.cache_controller = None
+            return  # early return if hicache is not used
+
+        raise NotImplementedError("Host cache is not supported yet")
+
+    def reset(self):
+        if self.cache_controller is not None:
+            # need to clear the acks before resetting the cache controller
+            raise NotImplementedError("Host cache is not supported yet")
+        self.tree.reset()
+
+    def match_prefix(self, key: List[int], **kwargs) -> MatchResult:
+        device_indices_vec, host_indices_length, node_gpu, node_cpu = (
+            self.tree.match_prefix(key)
+        )
+        return MatchResult(
+            device_indices=self._merge_tensor(device_indices_vec),
+            last_device_node=node_gpu,
+            last_host_node=node_cpu,
+            host_hit_length=host_indices_length,
+        )
+
+    def _insert(self, key: List[int], value: torch.Tensor) -> int:
+        """
+        Insert a key-value pair into the radix tree.
+        Args:
+            key (List[int]): The key to insert, represented as a list of integers.
+            value (torch.Tensor): The value to associate with the key.
+        Returns:
+            int: Number of device indices that were already present in the tree before the insertion.
+        """
+        ongoing_write, length = self.tree.writing_through(key, value)
+        if self.cache_controller is None:
+            assert len(ongoing_write) == 0, "Implementation error"
+            return length
+
+        raise NotImplementedError("Host cache is not supported yet")
+
+    def dec_lock_ref(self, node: TreeNodeCpp):
+        """
+        Decrement the reference count of a node to root of the radix tree.
+        Args:
+            node (TreeNodeCpp): The handle of the node to decrement the reference count for.
+        """
+        self.tree.lock_ref(node, False)  # do not increment
+
+    def inc_lock_ref(self, node: TreeNodeCpp):
+        """
+        Increment the reference count of from a node to root of the radix tree.
+        Args:
+            node (TreeNodeCpp): The handle of the node to increment the reference count for.
+        """
+        self.tree.lock_ref(node, True)
+
+    def evict(self, num_tokens: int):
+        evicted_device_indices = self.tree.evict(num_tokens)
+        for indice in evicted_device_indices:
+            self.token_to_kv_pool.free(indice)
+
+    def evictable_size(self):
+        return self.tree.evictable_size()
+
+    def protected_size(self):
+        return self.tree.protected_size()
+
+    def total_size(self):
+        return self.tree.total_size()
+
+    def cache_finished_req(self, req: Req):
+        """Cache request when it finishes."""
+        assert req.req_pool_idx is not None
+        token_ids = (req.origin_input_ids + req.output_ids)[:-1]
+        overall_len = len(token_ids)  # prefill + decode
+        kv_indices = self.req_to_token_pool.req_to_token[req.req_pool_idx, :overall_len]
+
+        # NOTE: our C++ implementation don't need `token_ids` and `kv_indices` to be page-aligned
+        # it will automatically align them, but length of them should be equal
+        old_prefix_len = len(req.prefix_indices) // self.page_size * self.page_size
+        new_prefix_len = self._insert(token_ids, kv_indices)
+
+        # NOTE: kv_indices[:old_prefix_len] == req.prefix_indices
+        assert old_prefix_len <= new_prefix_len, "Wrong prefix indices"
+
+        # KVCache between old & new is newly generated, but already exists in the pool
+        # we need to free this newly generated kv indices
+        if old_prefix_len < new_prefix_len:
+            self.token_to_kv_pool.free(kv_indices[old_prefix_len:new_prefix_len])
+
+        # need to free the unaligned part, since it cannot be inserted into the radix tree
+        if self.page_size != 1 and (  # unaligned tail only exists when page_size > 1
+            (unaligned_len := overall_len % self.page_size) > 0
+        ):
+            # NOTE: sglang PagedAllocator support unaligned free (which will automatically align it)
+            self.token_to_kv_pool.free(kv_indices[overall_len - unaligned_len :])
+
+        # Remove req slot release the cache lock
+        self.dec_lock_ref(req.last_node)
+        self.req_to_token_pool.free(req.req_pool_idx)
+
+    def cache_unfinished_req(self, req: Req):
+        """Cache request when it is unfinished."""
+        assert req.req_pool_idx is not None
+        token_ids = req.fill_ids
+        prefill_len = len(token_ids)  # prefill only (maybe chunked)
+        kv_indices = self.req_to_token_pool.req_to_token[req.req_pool_idx, :prefill_len]
+
+        # NOTE: our C++ implementation don't need `token_ids` and `kv_indices` to be page-aligned
+        # it will automatically align them, but length of them should be equal
+        old_prefix_len = len(req.prefix_indices) // self.page_size * self.page_size
+        new_prefix_len = self._insert(token_ids, kv_indices)
+
+        # NOTE: kv_indices[:old_prefix_len] == req.prefix_indices
+        assert old_prefix_len <= new_prefix_len, "Wrong prefix indices"
+
+        # TODO(dark): optimize the `insert` and `match` (e.g. merge into 1 function)
+        # The prefix indices need to updated to reuse the kv indices in the pool
+        new_indices_vec, _, new_last_node, _ = self.tree.match_prefix(token_ids)
+        new_indices = self._merge_tensor(new_indices_vec)
+        assert new_prefix_len <= len(new_indices)
+
+        # KVCache between old & new is newly generated, but already exists in the pool
+        # we need to free this newly generated kv indices and reuse the indices in the pool
+        if old_prefix_len < new_prefix_len:
+            self.token_to_kv_pool.free(kv_indices[old_prefix_len:new_prefix_len])
+            reused_indices = new_indices[old_prefix_len:new_prefix_len]
+            self.req_to_token_pool.req_to_token[
+                req.req_pool_idx, old_prefix_len:new_prefix_len
+            ] = reused_indices
+
+        if req.last_node != new_last_node:
+            self.dec_lock_ref(req.last_node)
+            self.inc_lock_ref(new_last_node)
+
+        # NOTE: there might be unaligned tail, so we may need to append it
+        assert len(new_indices) <= prefill_len < len(new_indices) + self.page_size
+        if self.page_size != 1 and len(new_indices) < prefill_len:
+            req.prefix_indices = torch.cat(
+                [new_indices, kv_indices[len(new_indices) :]]
+            )
+        else:
+            req.prefix_indices = new_indices
+        req.last_node = new_last_node
+
+    def pretty_print(self):
+        return self.tree.debug_print()

test/srt/test_cpp_radix_cache.py

@@ -0,0 +1,47 @@
+import os
+import unittest
+from types import SimpleNamespace
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.run_eval import run_eval
+from sglang.test.test_utils import (
+    DEFAULT_MODEL_NAME_FOR_TEST,
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    popen_launch_server,
+)
+
+
+class TestCppRadixCache(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        os.environ["SGLANG_EXPERIMENTAL_CPP_RADIX_TREE"] = "1"
+        cls.model = DEFAULT_MODEL_NAME_FOR_TEST
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_mmlu(self):
+        args = SimpleNamespace(
+            base_url=self.base_url,
+            model=self.model,
+            eval_name="mmlu",
+            num_examples=64,
+            num_threads=32,
+        )
+
+        metrics = run_eval(args)
+        print(metrics)
+        self.assertGreaterEqual(metrics["score"], 0.65)
+
+
+if __name__ == "__main__":
+    unittest.main()