update crei presentation.

doc/crei2013/gpundarray.txt

@@ -6,6 +6,7 @@ GpuNdArray
 **********
 
 Why a common GPU ndarray?
+-------------------------
 
 - Currently there are at least 4 different GPU array data structures in use by Python packages
 
@@ -23,6 +24,7 @@ Why a common GPU ndarray?
 
 
 Design Goals
+------------
 
 - Make it VERY similar to ``numpy.ndarray``
 - Be compatible with both CUDA and OpenCL
@@ -31,10 +33,10 @@ Design Goals
   - We want people from C, C++, Ruby, R, ... all use the same base GPU N-dimensional array
 
 
-Final GpuNdArray Note
+Final Note
+----------
 
 - Under development
-- Will be the next GPU array container for Theano (this summer!)
+- Will be the next GPU array container for Theano (*this summer!*)
 - Probably also for PyCUDA, PyOpenCL
 - Mailing list: http://lists.tiker.net/listinfo/gpundarray
-

doc/crei2013/index.txt

@@ -67,5 +67,5 @@ from gurus on hand if you get stuck.
     introduction
     theano
     advanced_theano
-    /tutorial/extending_theano
     gpundarray
+    /tutorial/extending_theano

doc/crei2013/introduction.txt

@@ -330,9 +330,6 @@ Project status
 
 
 
-TODO: Do I keep the GPU section?
-
-
 
 Why scripting for GPUs?
 -----------------------
@@ -398,34 +395,3 @@ How Fast are GPUs?
  * Theano can be linked with multi-core capable BLAS (GEMM and GEMV)
 
 * If you see speedup > 100x, the benchmark is probably not fair.
-
-
-Software for Directly Programming a GPU
----------------------------------------
-
-Theano is a meta-programmer, doesn't really count.
-
-* CUDA: C extension by NVIDIA 
-
- * Vendor-specific
-
- * Numeric libraries (BLAS, RNG, FFT) maturing.
-
-* OpenCL: multi-vendor version of CUDA
-
- * More general, standardized
-
- * Fewer libraries, less adoption.
-
-* PyCUDA: python bindings to CUDA driver interface
-
- * Python interface to CUDA
-
- * Memory management of GPU objects
-
- * Compilation of code for the low-level driver
-
- * Makes it easy to do GPU meta-programming from within Python
-
-* PyOpenCL: PyCUDA for PyOpenCL
-