diff --git a/cmake/Dependencies.cmake b/cmake/Dependencies.cmake
index f984bbebfab..e53eef3ec4a 100644
--- a/cmake/Dependencies.cmake
+++ b/cmake/Dependencies.cmake
@@ -1834,8 +1834,6 @@ if(USE_KINETO)
       set(CUPTI_LIB_NAME "cupti.lib")
     endif()
 
-    set(NVPERF_HOST_LIB_NAME "libnvperf_host.so")
-
     find_library(CUPTI_LIBRARY_PATH ${CUPTI_LIB_NAME} PATHS
         ${CUDA_SOURCE_DIR}
         ${CUDA_SOURCE_DIR}/extras/CUPTI/lib64
@@ -1850,27 +1848,13 @@ if(USE_KINETO)
         ${CUDA_SOURCE_DIR}/include
         NO_DEFAULT_PATH)
 
-    find_library(NVPERF_HOST_LIBRARY_PATH ${NVPERF_HOST_LIB_NAME} PATHS
-        ${CUDA_SOURCE_DIR}
-        ${CUDA_SOURCE_DIR}/lib
-        ${CUDA_SOURCE_DIR}/lib64
-        ${CUDA_SOURCE_DIR}/extras/CUPTI/lib64
-        NO_DEFAULT_PATH)
-
     if(CUPTI_LIBRARY_PATH AND CUPTI_INCLUDE_DIR)
       message(STATUS "  CUPTI_INCLUDE_DIR = ${CUPTI_INCLUDE_DIR}")
       set(CUDA_cupti_LIBRARY ${CUPTI_LIBRARY_PATH})
       message(STATUS "  CUDA_cupti_LIBRARY = ${CUDA_cupti_LIBRARY}")
-      # CUPTI Range Profiler requires the NVPerf library
-      # for configuring metrics
-      if(NVPERF_HOST_LIBRARY_PATH)
-        set(CUDA_nvperf_host_LIBRARY ${NVPERF_HOST_LIBRARY_PATH})
-        message(STATUS "  CUDA_nvperf_host_LIBRARY = ${NVPERF_HOST_LIBRARY_PATH}")
-      endif()
       message(STATUS "Found CUPTI")
       set(LIBKINETO_NOCUPTI OFF CACHE STRING "" FORCE)
 
-
       # I've only tested this sanity check on Linux; if someone
       # runs into this bug on another platform feel free to
       # generalize it accordingly
diff --git a/test/profiler/test_profiler.py b/test/profiler/test_profiler.py
index a29cb1bcf62..87df89f04d5 100644
--- a/test/profiler/test_profiler.py
+++ b/test/profiler/test_profiler.py
@@ -699,48 +699,6 @@ class TestProfiler(TestCase):
         if torch.cuda.is_available():
             check_metrics(stats, "device_memory_usage", deallocs=["[memory]"])
 
-    @unittest.skipIf(not kineto_available(), "Kineto is required")
-    @unittest.skipIf(not torch.cuda.is_available(), "CUDA is required")
-    def test_kineto_cupti_range_profiler(self):
-        """CUPTI provides a newer Profiling API from CUDA 10.0 that enables measuring
-        performance events for the GPU. This is supported as an experimental pytorch profiler feature.
-        Read more here https://docs.nvidia.com/cupti/r_main.html#r_profiler.
-        """
-        exp_config = _ExperimentalConfig(
-            profiler_metrics=[
-                # Metrics list at https://docs.nvidia.com/cupti/r_main.html#r_profiler
-                # or use kineto__tensor_core_insts, kineto__cuda_core_flops
-                "kineto__tensor_core_insts",
-                "dram__bytes_read.sum",
-                "dram__bytes_write.sum",
-            ],
-            profiler_measure_per_kernel=True,
-        )
-        with _profile(
-            use_cuda=True, use_kineto=True, experimental_config=exp_config
-        ) as p:
-            self.payload(use_cuda=True)
-
-        def check_trace(fname):
-            with open(fname) as f:
-                trace = json.load(f)
-                self.assertTrue("traceEvents" in trace)
-                events = trace["traceEvents"]
-                found_cupti_profiler_events = False
-                for evt in events:
-                    self.assertTrue("name" in evt)
-                    if "__cupti_profiler__" in evt["name"]:
-                        found_cupti_profiler_events = True
-                # PyTorch OSS CI runs in docker containers where the Range Profiler
-                # does not have sufficient privilege level (CUPTI_ERROR_INSUFFICIENT_PRIVILEGES).
-                # We can check that the profiler does not crash the job and the trace is not
-                # malformed, however do not check the actual presence of data.
-                self.assertTrue(1 or found_cupti_profiler_events)
-
-        with TemporaryFileName(mode="w+") as fname:
-            p.export_chrome_trace(fname)
-            check_trace(fname)
-
     @unittest.skipIf(
         IS_JETSON, "Jetson has a guard against OOM since host and gpu memory are shared"
     )