takagi

#include <cassert>
#include <iostream>
#include <thread>

__global__ void vecAddOne(float *a, int n) {
    int id = blockIdx.x * blockDim.x + threadIdx.x;
    if (id < n)
        a[id] += 1.0f;
}

takagi

diff --git a/cupyx/scipy/interpolate/_interpolate.py b/cupyx/scipy/interpolate/_interpolate.py
index bab74671e..ec3c5bcac 100644
--- a/cupyx/scipy/interpolate/_interpolate.py
+++ b/cupyx/scipy/interpolate/_interpolate.py
@@ -22,7 +22,7 @@ INTERVAL_KERNEL = r'''
 extern "C" {
 __global__ void find_breakpoint_position(
         const double* breakpoints, const double* x, long long* out,
-        bool extrapolate, int total_x, int total_breakpoints, bool asc) {
+        bool extrapolate, int total_x, int total_breakpoints, const bool* pasc) {

takagi

A tool to generate files for C extensions of CUDA-relatged libraries for CuPy. Currently covered are cuBLAS, cuSPARSE, and cuSOLVER, which have so many APIs to write their extensions by hands.

Usage

Generate files for all of the libraries

./gen.sh

takagi

{
    "_nodetype": "FileAST",
    "coord": null,
    "ext": [
        {
            "_nodetype": "Pragma",
            "coord": "../utils/fake_libc_include/_fake_typedefs.h:56:9",
            "string": "GCC diagnostic ignored \"-Wunused-function\""
        },
        {

takagi

import multiprocessing

import cupy
from cupy import cuda
from cupy.cuda import nccl
from cupy import testing

def f(n_devices, device, comm_id, rank):
    device.use()
    comm = nccl.NcclCommunicator(n_devices, comm_id, rank)

takagi

$ CHAINER_DTYPE=float16 python train_ptb.py -d 0 -e 10
#vocab = 10000
epoch       iteration   perplexity  val_perplexity
0           500         326440
0           1000        301342
1           1500        298940      inf
1           2000        334369
1           2500        334369
2           3000        306202      inf
2           3500        339762

takagi

$ CHAINER_DTYPE=float16 python postagging.py -d 0
[nltk_data] Downloading package brown to /home/ext-
[nltk_data]     mtakagi/nltk_data...
[nltk_data]   Package brown is already up-to-date!
# of sentences: 57340
# of words: 56057
# of pos: 472
epoch       main/loss   validation/main/loss  main/accuracy  validation/main/accuracy  elapsed_time
0           244.875                                                                    18.3736
0           373.75                                                                     34.9924

takagi

$ CHAINER_DTYPE=float16 python train_memnn.py tasks_1-20_v1-2/en-10k/qa1_single-supporting-fact_train.txt tasks_1-20_v1-2/en-10k/qa1_single-supporting-fact_test.txt -d 0
Training data: tasks_1-20_v1-2/en-10k/qa1_single-supporting-fact_train.txt: 2000
Test data: tasks_1-20_v1-2/en-10k/qa1_single-supporting-fact_test.txt: 200
epoch       main/loss   validation/main/loss  main/accuracy  validation/main/accuracy
1           nan         nan                   0.0017004      0
2           nan         nan                   0              0
3           nan         nan                   0              0
4           nan         nan                   0              0
5           nan         nan                   0              0
6           nan         nan                   0              0

takagi

$ CHAINER_DTYPE=float16 python train_mnist.py -d 0
Device: @cupy:0
# unit: 1000
# Minibatch-size: 100
# epoch: 20

epoch       main/loss   validation/main/loss  main/accuracy  validation/main/accuracy  elapsed_time
1           nan         nan                   0.0994271      0.0980225                 3.91818
2           nan         nan                   0.0997917      0.0980225                 6.22553
3           nan         nan                   0.0995833      0.0980225                 8.72424

takagi

$ CHAINER_DTYPE=float16 python train_dcgan.py -d 0
Device: @cupy:0
# Minibatch-size: 50
# n_hidden: 100
# epoch: 1000

epoch       iteration   gen/loss    dis/loss  ................]  0.01%
0           100         nan         nan
0           200         nan         nan
0           300         nan         nan