diff --git a/csrc/host_ir/lower.cpp b/csrc/host_ir/lower.cpp
index b188a14b47c..0c9ee7b061a 100644
--- a/csrc/host_ir/lower.cpp
+++ b/csrc/host_ir/lower.cpp
@@ -27,44 +27,6 @@
 
 namespace nvfuser {
 
-bool HostIrLower::canLower(Expr* expr, bool ignore_inner_resharding) {
-  if (!isResharding(expr)) {
-    return true;
-  }
-  if (!ir_utils::isTvOp(expr)) {
-    return false;
-  }
-  if (auto* reduction = dynamic_cast<ReductionOp*>(expr)) {
-    if (!ignore_inner_resharding && !isCommunicationLayoutCompliant(expr)) {
-      return false;
-    }
-    auto in = reduction->in()->as<TensorView>();
-    auto out = reduction->out()->as<TensorView>();
-    // get the reduced axis
-    std::vector<IterDomain*> reduction_axis;
-    std::copy_if(
-        out->getLogicalDomain().begin(),
-        out->getLogicalDomain().end(),
-        std::back_inserter(reduction_axis),
-        [](IterDomain* id) { return id->isReduction(); });
-    // check whether the reduction involves only one axis
-    if (reduction_axis.size() != 1) {
-      return false;
-    }
-    // We check whether the reduced axis is sharded on the input
-    const auto c2p_map =
-        PairwiseLogicalDomainMap(in, out).mapConsumerToProducer();
-    auto c2p_map_it = c2p_map.find(reduction_axis.at(0));
-    return c2p_map_it != c2p_map.end() && c2p_map_it->second->isDeviceDim();
-  } else if (auto* ldst = dynamic_cast<LoadStoreOp*>(expr)) {
-    if (!ignore_inner_resharding && !isCommunicationLayoutCompliant(expr)) {
-      return false;
-    }
-    return ldst->as<LoadStoreOp>()->opType() == LoadStoreOpType::Set;
-  }
-  return false;
-}
-
 bool HostIrLower::isLowerableAsStandaloneHostOp(Expr* expr) {
   if (expr->isOneOf<
           MatmulOp,
diff --git a/csrc/host_ir/lower.h b/csrc/host_ir/lower.h
index 8df156d4512..8bc4f37eca2 100644
--- a/csrc/host_ir/lower.h
+++ b/csrc/host_ir/lower.h
@@ -24,11 +24,6 @@ class HostIrLower {
   explicit HostIrLower(const HostIrLowerParams& params = HostIrLowerParams())
       : params_(params) {}
 
-  // The flag `ignore_inner_resharding` is useful because the preseg passes
-  // `InsertReshardingsPass` and `ReorderShardedAxisPass` want different
-  // behaviors
-  static bool canLower(Expr* expr, bool ignore_inner_resharding = false);
-
   // Lower a sharded Expr into a series of Communication.
   std::vector<Expr*> lower(Expr* c, DeviceIdxType my_device_index);