Update frontpage.html

ksbsk · Dec 9, 2019 · 98fc431 · 98fc431
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diff --git a/chapter_computational-performance/multiple-gpus.md b/chapter_computational-performance/multiple-gpus.md
@@ -28,9 +28,10 @@ Assume there are $k$ GPUs on a machine. Given the model to be trained, each GPU
 
 In order to implement data parallelism in a multi-GPU training scenario from scratch, we first import the required packages or modules.
 
-```{.python .input  n=33}
+```{.python .input  n=2}
 %matplotlib inline
 import d2l
+import mxnet as mx
 from mxnet import autograd, nd, gluon
 ```
 
@@ -120,7 +121,7 @@ Now, we try to divide the 6 data instances equally between 2 GPUs using the `spl
 
 ```{.python .input  n=8}
 data = nd.arange(24).reshape((6, 4))
-ctx = d2l.try_all_gpus()
+ctx = [mx.gpu(0), mx.gpu(1)]
 splitted = gluon.utils.split_and_load(data, ctx)
 print('input: ', data)
 print('load into', ctx)

diff --git a/static/frontpage/frontpage.html b/static/frontpage/frontpage.html
@@ -213,6 +213,7 @@ <h3>D2L as a textbook or a reference book</h3>
     Indian Institute of Technology Kanpur (India)<br>
     Indian Institute of Technology Ropar (India)<br>
     Kyungpook National University (Korea)<br>
+    Massachusetts Institute of Technology (USA)<br>
     Shanghai Jiao Tong University (China)<br>
     Shanghai University of Finance and Economics (China)<br>
     Texas A&amp;M University (USA)<br>