numba-pro

How to use numba in Colaboratory

由 拜拜、爱过 提交于 2020-12-29 06:56:54
问题 Anybody tried to use numba in google collaboratory? I just can not figure out how to set it up in this environment. At the moment, I'm stuck with the error library nvvm not found . 回答1: Copy this code into cell. It works for me. !apt-get install nvidia-cuda-toolkit !pip3 install numba import os os.environ['NUMBAPRO_LIBDEVICE'] = "/usr/lib/nvidia-cuda-toolkit/libdevice" os.environ['NUMBAPRO_NVVM'] = "/usr/lib/x86_64-linux-gnu/libnvvm.so" from numba import cuda import numpy as np import time

Using numba for cosine similarity between a vector and rows in a matix

由 扶醉桌前 提交于 2019-12-23 03:35:11
问题 Found this gist using numba for fast computation of cosine similarity. import numba @numba.jit(target='cpu', nopython=True) def fast_cosine(u, v): m = u.shape[0] udotv = 0 u_norm = 0 v_norm = 0 for i in range(m): if (np.isnan(u[i])) or (np.isnan(v[i])): continue udotv += u[i] * v[i] u_norm += u[i] * u[i] v_norm += v[i] * v[i] u_norm = np.sqrt(u_norm) v_norm = np.sqrt(v_norm) if (u_norm == 0) or (v_norm == 0): ratio = 1.0 else: ratio = udotv / (u_norm * v_norm) return ratio Results look

NumbaPro on Cuda device over ssh connection

由 左心房为你撑大大i 提交于 2019-12-20 04:38:18
问题 I'm using Python/NumbaPro to use my CUDA complient GPU on a windows box. I use Cygwin as shell and from within a cygwin console it has no problems finding my CUDA device. I test with the simple command numbapro.check_cuda() But when I'm connection to the box over OpenSSH (as part of my Cygwin setup), I get the following error: numba.cuda.cudadrv.error.CudaSupportError: Error at driver init: Call to cuInit results in CUDA_ERROR_NO_DEVICE: How to fix this? 回答1: The primary cause of this is

CudaAPIError: [1] Call to cuLaunchKernel results in CUDA_ERROR_INVALID_VALUE in Python

由 荒凉一梦 提交于 2019-12-20 03:11:00
问题 I'm having this error when trying to run this code in Python using CUDA. I'm following this tutorial but i'm trying it in Windows 7 x64 machine. https://www.youtube.com/watch?v=jKV1m8APttU In fact, I run check_cuda() and all tests passed. Can anyone help me what is the exact issue here. My Code: import numpy as np from timeit import default_timer as timer from numbapro import vectorize, cuda @vectorize(['float64(float64, float64)'], target='gpu') def VectorAdd(a, b): return a + b def main():

get wrong result when caculating on GPU (python3.5+numba+CUDA8.0)

由 你离开我真会死。 提交于 2019-12-13 10:09:30
问题 I want to get the sum of different parts of an array. I run my code. and find two problems from what was printed. pro1: Described in detail here. It has been solved. Maybe it's not a real problem. pro2: In my code, I gived different value to sbuf[0,2], sbuf[1,2], sbuf[2,2] and sbuf[0,3], sbuf[1,3], sbuf[2,3]. But find that after cuda.syncthreads() , the values bacame same between sbuf[0,2] and sbuf[0,3], sbuf[1,2] and sbuf[1,3], sbuf[2,2] and sbuf[2,3]. It directly lead to the values of Xi_s,

Cannot coerce to or from object in nopython context: Error after python

由 做~自己de王妃 提交于 2019-12-11 16:31:47
问题 Following up from here, Numba is finally working (after weeks) on my machine, without any weird indentation errors. I've implemented it as in the solution to the linked question. However, I now get this string of errors from Numba, the last line being that it can't coerce to or from object in nopython context : Traceback (most recent call last): File "C:\Users\app\Documents\Python Scripts\gbc_classifier_train.py", line 19, in <module> import gentleboost_c_class_jit_v6_nolimit as gbc File "C:

no module named numbapro

由 纵然是瞬间 提交于 2019-12-06 16:35:26
问题 I ran this code I read on a CUDA Python intro page:- import numpy as np from timeit import default_timer as timer from numbapro import vectorize @vectorize(["float32(float32, float32)"], target='gpu') def VectorAdd(a, b): return a + b def main(): N = 32000000 A = np.ones(N, dtype=np.float32) B = np.ones(N, dtype=np.float32) C = np.zeros(N, dtype=np.float32) start = timer() C = VectorAdd(A, B) vectoradd_timer = timer() - start print("C[:5] = " + str(C[:5])) print("C[-5:] = " + str(C[-5:]))

NumbaPro on Cuda device over ssh connection

由 蓝咒 提交于 2019-12-02 07:18:04
I'm using Python/NumbaPro to use my CUDA complient GPU on a windows box. I use Cygwin as shell and from within a cygwin console it has no problems finding my CUDA device. I test with the simple command numbapro.check_cuda() But when I'm connection to the box over OpenSSH (as part of my Cygwin setup), I get the following error: numba.cuda.cudadrv.error.CudaSupportError: Error at driver init: Call to cuInit results in CUDA_ERROR_NO_DEVICE: How to fix this? talonmies The primary cause of this is Windows service session 0 isolation. When you run any application via a service which runs in session

why can't I get the right sum of 1D array with numba (cuda python)?

由 扶醉桌前 提交于 2019-11-27 16:28:59
I try to use cuda python with numba. The code is to calculate the sum of a 1D array as follows, but I don't know how to get one value result rather than three values. python3.5 with numba + CUDA8.0 import os,sys,time import pandas as pd import numpy as np from numba import cuda, float32 os.environ['NUMBAPRO_NVVM']=r'D:\NVIDIA GPU Computing Toolkit\CUDA\v8.0\nvvm\bin\nvvm64_31_0.dll' os.environ['NUMBAPRO_LIBDEVICE']=r'D:\NVIDIA GPU Computing Toolkit\CUDA\v8.0\nvvm\libdevice' bpg = (1,1) tpb = (1,3) @cuda.jit def calcu_sum(D,T): ty = cuda.threadIdx.y bh = cuda.blockDim.y index_i = ty L = len(D)

why can't I get the right sum of 1D array with numba (cuda python)?

由 ⅰ亾dé卋堺 提交于 2019-11-27 04:08:21
问题 I try to use cuda python with numba. The code is to calculate the sum of a 1D array as follows, but I don't know how to get one value result rather than three values. python3.5 with numba + CUDA8.0 import os,sys,time import pandas as pd import numpy as np from numba import cuda, float32 os.environ['NUMBAPRO_NVVM']=r'D:\NVIDIA GPU Computing Toolkit\CUDA\v8.0\nvvm\bin\nvvm64_31_0.dll' os.environ['NUMBAPRO_LIBDEVICE']=r'D:\NVIDIA GPU Computing Toolkit\CUDA\v8.0\nvvm\libdevice' bpg = (1,1) tpb =
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