Applied suggestions from comments by @csbnw

kernel_tuner/backends/cupy.py

@@ -47,7 +47,6 @@ def __init__(self, device=0, iterations=7, compiler_options=None, observers=None
         self.devprops = dev.attributes
         self.cc = dev.compute_capability
         self.max_threads = self.devprops["MaxThreadsPerBlock"]
-        self.cache_size_L2 = self.devprops["L2CacheSize"]
 
         self.iterations = iterations
         self.current_module = None
@@ -126,7 +125,7 @@ def compile(self, kernel_instance):
         compiler_options = self.compiler_options
         if not any(["-std=" in opt for opt in self.compiler_options]):
             compiler_options = ["--std=c++11"] + self.compiler_options
-        # CuPy already sets the --gpu-architecture by itself, as per https://github.com/cupy/cupy/blob/20ccd63c0acc40969c851b1917dedeb032209e8b/cupy/cuda/compiler.py#L145
+        # CuPy already sets the --gpu-architecture by itself, as per https://github.com/cupy/cupy/blob/main/cupy/cuda/compiler.py#L145
 
         options = tuple(compiler_options)
 

kernel_tuner/backends/hip.py

@@ -59,7 +59,6 @@ def __init__(self, device=0, iterations=7, compiler_options=None, observers=None
 
         self.name = self.hipProps._name.decode('utf-8')
         self.max_threads = self.hipProps.maxThreadsPerBlock
-        self.cache_size_L2 = self.hipProps.l2CacheSize
         self.device = device
         self.compiler_options = compiler_options or []
         self.iterations = iterations

kernel_tuner/backends/nvcuda.py

@@ -68,10 +68,6 @@ def __init__(self, device=0, iterations=7, compiler_options=None, observers=None
             cudart.cudaDeviceAttr.cudaDevAttrMaxThreadsPerBlock, device
         )
         cuda_error_check(err)
-        err, self.cache_size_L2 = cudart.cudaDeviceGetAttribute(
-            cudart.cudaDeviceAttr.cudaDevAttrL2CacheSize, device
-        )
-        cuda_error_check(err)
         self.cc = f"{major}{minor}"
         self.iterations = iterations
         self.current_module = None

kernel_tuner/backends/opencl.py

@@ -45,10 +45,6 @@ def __init__(
         self.max_threads = self.ctx.devices[0].get_info(
             cl.device_info.MAX_WORK_GROUP_SIZE
         )
-        # TODO the L2 cache size request fails
-        # self.cache_size_L2 = self.ctx.devices[0].get_info(
-        #     cl.device_affinity_domain.L2_CACHE
-        # )
         self.compiler_options = compiler_options or []
 
         # observer stuff

kernel_tuner/backends/pycuda.py

@@ -101,7 +101,6 @@ def _finish_up():
             str(k): v for (k, v) in self.context.get_device().get_attributes().items()
         }
         self.max_threads = devprops["MAX_THREADS_PER_BLOCK"]
-        self.cache_size_L2 = devprops["L2_CACHE_SIZE"]
         cc = str(devprops.get("COMPUTE_CAPABILITY_MAJOR", "0")) + str(
             devprops.get("COMPUTE_CAPABILITY_MINOR", "0")
         )

kernel_tuner/core.py

@@ -340,62 +340,14 @@ def __init__(
         if not quiet:
             print("Using: " + self.dev.name)
 
-        if lang.upper() not in ['OPENCL', 'C', 'FORTRAN']:
-            # flush the L2 cache, inspired by https://github.com/pytorch/FBGEMM/blob/eb3c304e6c213b81f2b2077813d3c6d16597aa97/fbgemm_gpu/bench/verify_fp16_stochastic_benchmark.cu#L130
-            flush_gpu_string = """
-            __global__ void flush_gpu(char* d_flush, char* d_flush2, bool do_write) {
-                    const int idx = blockIdx.x * blockDim.x + threadIdx.x;
-                    const char val = d_flush[idx];
-                    if (do_write * val) {
-                        d_flush2[idx] = val;
-                }
-            }
-            """
-            cache_size = self.dev.cache_size_L2
-            d_flush = np.ones((cache_size), order='F').astype(np.float32)
-            d_flush2 = np.ones((cache_size), order='F').astype(np.float32)
-            self.flush_kernel_gpu_args = [d_flush, d_flush2, np.int32(True)]
-
-            from kernel_tuner.interface import Options
-            options = {
-                'kernel_name': 'flush_gpu',
-                'lang': 'CUDA',
-                'arguments': self.flush_kernel_gpu_args,
-                'problem_size': cache_size,
-                'grid_div_x': None,
-                'grid_div_y': None,
-                'grid_div_z': None,
-                'block_size_names': None,
-            }
-            options = Options(options)
-            flush_kernel_lang = lang.upper() if lang.upper() in ['CUDA', 'CUPY', 'NVCUDA'] else 'CUPY'
-            flush_kernel_source = KernelSource('flush_gpu', flush_gpu_string, flush_kernel_lang)
-            self.flush_kernel_instance = self.create_kernel_instance(flush_kernel_source, kernel_options=options, params=dict(), verbose=not quiet)
-            self.flush_kernel = self.compile_kernel(self.flush_kernel_instance, verbose=not quiet)
-            self.flush_kernel_gpu_args = self.ready_argument_list(self.flush_kernel_gpu_args)
-
-            # from kernel_tuner.kernelbuilder import PythonKernel
-            # self.flush_kernel = PythonKernel('flush_gpu', flush_gpu_string, cache_size, self.flush_kernel_gpu_args)
-
-    def flush_cache(self):
-        """This special function can be called to flush the L2 cache."""
-        if hasattr(self, 'flush_kernel'):
-            return
-            self.dev.synchronize()
-            assert self.run_kernel(self.flush_kernel, self.flush_kernel_gpu_args, self.flush_kernel_instance)
-            # self.flush_kernel.run_kernel(self.flush_kernel.gpu_args)
-            self.dev.synchronize()
-
-    def benchmark_default(self, func, gpu_args, threads, grid, result, flush_cache=True):
-        """Benchmark one kernel execution at a time. Run with `flush_cache=True` to avoid caching effects between iterations."""
+    def benchmark_default(self, func, gpu_args, threads, grid, result):
+        """Benchmark one kernel execution at a time."""
         observers = [
             obs for obs in self.dev.observers if not isinstance(obs, ContinuousObserver)
         ]
 
         self.dev.synchronize()
         for _ in range(self.iterations):
-            if flush_cache:
-                self.flush_cache()
             for obs in observers:
                 obs.before_start()
             self.dev.synchronize()

test/test_pycuda_mocked.py

@@ -13,8 +13,7 @@ def setup_mock(drv):
     context = Mock()
     devprops = {'MAX_THREADS_PER_BLOCK': 1024,
                 'COMPUTE_CAPABILITY_MAJOR': 5,
-                'COMPUTE_CAPABILITY_MINOR': 5,
-                'L2_CACHE_SIZE': 4096}
+                'COMPUTE_CAPABILITY_MINOR': 5,}
     context.return_value.get_device.return_value.get_attributes.return_value = devprops
     context.return_value.get_device.return_value.compute_capability.return_value = "55"
     drv.Device.return_value.retain_primary_context.return_value = context()

test/test_util_functions.py

@@ -153,7 +153,7 @@ def test_to_valid_nvrtc_gpu_arch_cc():
     assert to_valid_nvrtc_gpu_arch_cc("40") == "52"
     assert to_valid_nvrtc_gpu_arch_cc("90b") == "90a"
     assert to_valid_nvrtc_gpu_arch_cc("91c") == "90a"
-    assert to_valid_nvrtc_gpu_arch_cc("10123001") == "52"
+    assert to_valid_nvrtc_gpu_arch_cc("1234") == "52"
     with pytest.raises(ValueError):
         assert to_valid_nvrtc_gpu_arch_cc("")
         assert to_valid_nvrtc_gpu_arch_cc("1")