update build doc

Makefile

@@ -71,6 +71,10 @@ ifneq ($(ADD_LDFLAGS), NONE)
 	LDFLAGS += $(ADD_LDFLAGS)
 endif
 
+ifneq ($(USE_CUDA_PATH), NONE)
+	NVCC=$(USE_CUDA_PATH)/bin/nvcc
+endif
+
 .PHONY: clean all test lint doc clean_all
 
 all: lib/libmxnet.a lib/libmxnet.so $(BIN)
@@ -105,7 +109,7 @@ lib/libmxnet.so: $(ALL_DEP)
 $(DMLC_CORE)/libdmlc.a:
 	+ cd $(DMLC_CORE); make libdmlc.a config=$(ROOTDIR)/$(config); cd $(ROOTDIR)
 
-bin/im2rec: tools/im2rec.cc $(DMLC_CORE)/libdmlc.a 
+bin/im2rec: tools/im2rec.cc $(DMLC_CORE)/libdmlc.a
 
 $(BIN) :
 	$(CXX) $(CFLAGS)  -o $@ $(filter %.cpp %.o %.c %.a %.cc, $^) $(LDFLAGS)

doc/build.md

@@ -1,19 +1,58 @@
 Build and Installation
 ======================
-- You can clone the mxnet from the [github repo](https://github.com/dmlc/mxnet)
-- After you clone the repo, update the submodules by
+
+Minimal system requirement:
+
+- recent c++ compiler supporting C++ 11 such as `g++ >= 4.8`
+- git
+- BLAS library.
+- opencv
+
+On Ubuntu >= 13.10, one can install them by
+
+```bash
+sudo apt-get update
+sudo apt-get install -y build-essential git libblas-dev libopencv-dev
+```
+
+Then build mxnet
+
+```bash
+git clone --recursive https://github.com/dmlc/mxnet
+cd mxnet; make -j4
+```
+
+To install the python package, first make sure `python >= 2.7` and `numpy >= ?` are installed, then
+
 ```bash
-git submodule init
+cd python; python setup.py install
+```
+
+If anything goes well, now we can train a multilayer perceptron on the hand
+digit recognition dataset.
+
+```bash
+cd ..; python tests/python/train/test_mlp.py
+```
+
+Advanced Build
+--------------
+
+- update the repo:
+
+```bash
+git pull
 git submodule update
 ```
-- Copy [make/config.mk](../make/config.mk) to the project root, modify according to your desired setting.
-- Type ```make``` in the root folder.
 
+- install python package in developing model,
 
-Install Python Package
-----------------------
-After you build the mxnet, you can install python package by
 ```bash
-cd python
-python setup.py install
+cd python; python setup.py develop --user
 ```
+
+- modify the compiling options such as compilers, CUDA, CUDNN, Intel MKL,
+various distributed filesystem such as HDFS/Amazon S3/...
+
+  First copy [make/config.mk](../make/config.mk) to the project root, then
+  modify the according flags.

doc/index.md

@@ -9,8 +9,8 @@ How to Get Started
 
 User Guide
 ----------
-* [Python Package Document](python/index.md)
 * [Build and Installation](build.md)
+* [Python Package Document](python/index.md)
 * [Frequently Asked Questions](faq.md)
 
 Developer Guide

make/config.mk

@@ -9,19 +9,33 @@
 #  - type make or make -j n for parallel build
 #----------------------------------------------------
 
+#------------------------
 # choice of compiler
+#------------------------
+
 export CC = gcc
 export CXX = g++
 export NVCC = nvcc
 
 # whether compile with debug
 DEBUG = 0
 
+# the additional link flags you want to add
+ADD_LDFLAGS =
+
+# the additional compile flags you want to add
+ADD_CFLAGS =
+
+#---------------------------------------------
+# matrix computation libraries for CPU/GPU
+#---------------------------------------------
+
 # whether use CUDA during compile
 USE_CUDA = 0
 
 # add the path to CUDA libary to link and compile flag
 # if you have already add them to enviroment variable, leave it as NONE
+# USE_CUDA_PATH = /usr/local/cuda
 USE_CUDA_PATH = NONE
 
 # whether use CUDNN R3 library
@@ -39,39 +53,32 @@ USE_OPENCV = 1
 # use openmp for parallelization
 USE_OPENMP = 1
 
-#
 # choose the version of blas you want to use
 # can be: mkl, blas, atlas, openblas
 USE_STATIC_MKL = NONE
 USE_BLAS = blas
-#
-# add path to intel libary, you may need it
-# for MKL, if you did not add the path to enviroment variable
-#
-USE_INTEL_PATH = NONE
 
-# the additional link flags you want to add
-ADD_LDFLAGS =
+# add path to intel libary, you may need it for MKL, if you did not add the path
+# to enviroment variable
+USE_INTEL_PATH = NONE
 
-# the additional compile flags you want to add
-ADD_CFLAGS =
-#
-# If use MKL, choose static link automaticly to fix python wrapper
-#
+# If use MKL, choose static link automaticly to allow python wrapper
 ifeq ($(USE_BLAS), mkl)
 	USE_STATIC_MKL = 1
 endif
 
-#------------------------
-# configuration for DMLC
-#------------------------
-# whether use HDFS support during compile
-# this will allow cxxnet to directly save/load model from hdfs
-USE_HDFS = 0
+#----------------------------
+# distributed filesystems
+#----------------------------
 
-# whether use AWS S3 support during compile
-# this will allow cxxnet to directly save/load model from s3
-USE_S3 = 1
+# whether or not allow to read and write HDFS directly. If yes, then hadoop is
+# required
+USE_HDFS = 0
 
-# path to libjvm.so
+# path to libjvm.so. required if USE_HDFS=1
 LIBJVM=$(JAVA_HOME)/jre/lib/amd64/server
+
+# whether or not allow to read and write AWS S3 directly. If yes, then
+# libcurl4-openssl-dev is required, it can be installed on Ubuntu by
+# sudo apt-get install -y libcurl4-openssl-dev
+USE_S3 = 0