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MESA: error: Use of VkSurfacePresentModeCompatibilityEXT without a VkSurfacePresentModeEXT set. This is an application bug.
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VULKANINFO
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Vulkan Instance Version: 1.3.253
Instance Extensions: count = 23
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name of display: :0
display: :0 screen: 0
direct rendering: Yes
server glx vendor string: SGI
server glx version string: 1.4
server glx extensions:
GLX_ARB_context_flush_control, GLX_ARB_create_context,
GLX_ARB_create_context_no_error, GLX_ARB_create_context_profile,
GLX_ARB_create_context_robustness, GLX_ARB_fbconfig_float,
GLX_ARB_framebuffer_sRGB, GLX_ARB_multisample,
amdgpu_device_initialize: amdgpu_query_info(ACCEL_WORKING) failed (-13)
amdgpu: amdgpu_device_initialize failed.
amdgpu_device_initialize: amdgpu_query_info(ACCEL_WORKING) failed (-13)
amdgpu: amdgpu_device_initialize failed.
EGL client extensions string:
EGL_EXT_client_extensions, EGL_EXT_device_base,
EGL_EXT_device_enumeration, EGL_EXT_device_query, EGL_EXT_platform_base,
EGL_EXT_platform_device, EGL_EXT_platform_wayland, EGL_EXT_platform_x11,
EGL_EXT_platform_xcb, EGL_KHR_client_get_all_proc_addresses,
EGL_KHR_debug, EGL_KHR_platform_gbm, EGL_KHR_platform_wayland,
@qwitwa
qwitwa / dask_numpy_hashing.py
Last active December 6, 2018 19:50
Performance when passing large numpy arrays to dask with and without hashing
import numpy as np
import dask.array as da
from dask.distributed import Client
client = Client()
# normal use case, shows some slowdown
def create_test_for_3d_array(x, y, z):
arr = np.random.rand(x, y, z)
def with_hashing():