diff --git a/csrc/host_ir/executor.cpp b/csrc/host_ir/executor.cpp
index 38906669367..1f8dc97bbfa 100644
--- a/csrc/host_ir/executor.cpp
+++ b/csrc/host_ir/executor.cpp
@@ -378,15 +378,13 @@ void HostIrEvaluator::handle(Wait* wait) {
 
 namespace {
 
-void allConsumerValsOfHelper(
-    Val* val,
-    std::unordered_set<Val*>& visisted_vals) {
-  if (visisted_vals.find(val) != visisted_vals.end()) {
+void allConsumerValsOfHelper(Val* val, std::unordered_set<Val*>& visited_vals) {
+  if (visited_vals.find(val) != visited_vals.end()) {
     return;
   }
-  visisted_vals.insert(val);
+  visited_vals.insert(val);
   for (Val* consumer : ir_utils::consumerValsOf(val)) {
-    allConsumerValsOfHelper(consumer, visisted_vals);
+    allConsumerValsOfHelper(consumer, visited_vals);
   }
 }
 
diff --git a/csrc/multidevice/communication.cpp b/csrc/multidevice/communication.cpp
index 29ef6995969..522b755b96d 100644
--- a/csrc/multidevice/communication.cpp
+++ b/csrc/multidevice/communication.cpp
@@ -66,12 +66,15 @@ void assertBuffersHaveSameSize(
   if (bufs1.empty() && bufs2.empty()) {
     return;
   }
-  const auto numel = (bufs1.empty() ? bufs2 : bufs1).at(0).numel();
+  const auto shape = (bufs1.empty() ? bufs2 : bufs1).at(0).sizes();
   for (const auto& bufs : {bufs1, bufs2}) {
     for (const auto& buf : bufs) {
       NVF_ERROR(
-          buf.numel() == numel,
-          "all buffers must have the same number of elements");
+          buf.sizes() == shape,
+          "all buffers must have the same shape, but got: ",
+          buf.sizes(),
+          " vs ",
+          shape);
     }
   }
 }
diff --git a/tests/cpp/test_multidevice_overlap.cpp b/tests/cpp/test_multidevice_overlap.cpp
index b9ca9ee5a91..e371a53dd4d 100644
--- a/tests/cpp/test_multidevice_overlap.cpp
+++ b/tests/cpp/test_multidevice_overlap.cpp
@@ -164,7 +164,7 @@ class OverlapTest : public MultiDeviceTest {
 
   void validate() {
     auto tc_expected = getExpectedResult();
-    auto tc_cpu = tc_.to(torch::kCPU);
+    auto tc_cpu = tc_.cpu();
     EXPECT_TRUE(tc_cpu.allclose(tc_expected, 1e-1, 1e-1))
         << "Unexpected results, obtained:" << tc_cpu
         << "\n expected: " << tc_expected;
@@ -837,18 +837,19 @@ TEST_F(AllgatherOverlapTest, AllgatherBasedPipeliningHostIrImplementation) {
       IrBuilder::create<hir::Stream>(stream_index));
 
   TensorView* tva_j = select(tva, 0, j);
+  TensorView* tva_j_unsqueezed = unsqueeze(tva_j, 0);
   TensorView* tva_allgathered_j = select(tva_allgathered, 0, j);
 
   // Setting the DeviceMesh of the communication's I/O is artificial but
   // required at this point
   DeviceMesh full_mesh(all_devices_);
   tva_allgathered_j->setDeviceMesh(full_mesh);
-  tva_j->setDeviceMesh(full_mesh);
+  tva_j_unsqueezed->setDeviceMesh(full_mesh);
 
   auto* communication = IrBuilder::create<Communication>(
       CommunicationType::Allgather,
       /*out=*/tva_allgathered_j,
-      /*in=*/tva_j,
+      /*in=*/tva_j_unsqueezed,
       /*team=*/all_devices_);
   auto* wait = IrBuilder::create<hir::Wait>(communication);
 
@@ -864,6 +865,7 @@ TEST_F(AllgatherOverlapTest, AllgatherBasedPipeliningHostIrImplementation) {
   std::vector<Expr*> loop_body = {
       set_stream,
       tva_j->definition(),
+      tva_j_unsqueezed->definition(),
       tva_allgathered_j->definition(),
       communication,
       wait,
@@ -899,9 +901,25 @@ TEST_F(AllgatherOverlapTest, AllgatherBasedPipeliningHostIrImplementation) {
   for_loop_stream->body().push_back(sync_stream);
   hic->pushBackTopLevelExprs(for_loop_stream);
 
-  // The following line is artificial but necessary to make
-  // tva_j->isProducerOf(tvc_j) == true
-  hic->addOutput(tvc_j);
+  // The following line is artificial but necessary to make tva_j_unsqueeze a
+  // consumer of tva_j.
+  //
+  // HostIrEvaluator::handle(ForLoop*) relies on `Val::uses()` to find all
+  // **transitive** consumers of the loop index `j`.  `tva_j_unsqueezed` is a
+  // bit special among all transitive consumers of `j`. It doesn't use `j`
+  // directly but uses `tva_j` which is a TensorView.  TensorView's uses are
+  // built lazily by Fusion::resetTvUses. For efficiency, Fusion::resetTvUses
+  // only fix TensorViews that can reach outputs. Therefore, we add
+  // tva_j_unsqueezed as an output.  Other TensorViews don't need this
+  // treatmenet because they are direct users of `j`, a scalar whose uses are
+  // built eagerly upon registration.
+  //
+  // We could have added `tvc_j` instead as an output, which transitively
+  // consumes `tva_j_unsqueezed`. However, `tvc_j` has two definitions, a Select
+  // and a MatmulOp, and StmtSort::getExprs only traverse via the first
+  // registered definition (i.e. the Select). This sounds like a bug -- I wonder
+  // how nvFuser resets the TensorView uses of a kir::Kernel, also non-SSA.
+  hic->addOutput(tva_j_unsqueezed);
 
   hir::HostIrEvaluator hie(std::move(hic), communicator_);