gdev: updated README

README

@@ -19,23 +19,25 @@
 Gdev is a rich set of open-source GPGPU runtime and driver software.
 Currently it supports NVIDIA GPUs but is also portable to other GPUs.
 The supported API implementaions include:
-1. "Gdev API": A low-level API to manage details of GPUs.
-2. "CUDA Driver API": A high-level API adovocated by NVIDIA, which is
-   built on top of Gdev API. 
-Leveraging Gdev API, you can add your favorite high-level API to Gdev
-other than CUDA Driver API. We will support CUDA Runtime API as well.
+  "Gdev API": A low-level API to manage details of GPUs.
+  "CUDA Driver API": A low-level API adovocated by NVIDIA.
+  "CUDA Runtime API": A high-level API adovocated by NVIDIA. 
+The implementation of CUDA Driver API and CUDA Runtime API is built
+on top of Gdev API. For CUDA Runtime API we make use of GPU Ocelot as
+a front-end implementation. You can add your favorite high-level API
+to Gdev other than CUDA Driver/Runtime APIs, leveraging Gdev API.
 
 Gdev provides runtime support in both the device driver and the user-
-space library. Runtime support in the device driver is unique to Gdev
-while most of existing GPGPU programming frameworks take user-space 
-approaches. It allows the OS to manage GPUs as first-class citizens
-and execute CUDA programs by itself, using loadable kernel modules.
+space library. Device-driver runtime support is a unique feature of
+Gdev while most existing GPGPU programming frameworks take user-space 
+approaches. With device-driver runtime support, Gdev allows the OS to
+manage GPUs as first-class citizens and execute CUDA programs itself.
 Gdev's user-space runtime support is also unique in a sense that it 
 is available for multiple open-source and proprietary device drivers.
 The supported device drivers include:
-1. "Nouveau": An open-source driver developed by the Linux community.
-2. "PSCNV": An open-source driver developed by PathScale.
-3. "NVRM": A proprietary binary driver provided by NVIDIA.
+  "Nouveau": An open-source driver developed by the Linux community.
+  "PSCNV": An open-source driver developed by PathScale.
+  "NVRM": A proprietary binary driver provided by NVIDIA.
 
 To summarize, Gdev offers the following advantages:
 - You have open-source access to GPGPU runtime and driver software.
@@ -63,13 +65,17 @@ Do you want to use user-space runtime with NVRM (NVIDIA Driver)?
 
 
 #####################################################################
-# Related research papers 
+# The publication of the Gdev project 
 #####################################################################
 
 S. Kato, M. McThrow, C. Maltzahn, and S. Brandt. "Gdev: First-Class
 GPU Resource Management in the Operating System", In Proceedings of 
 the 2012 USENIX Annual Technical Conference (USENIX ATC'12), 2012.
 
+#####################################################################
+# Related research papers 
+#####################################################################
+
 Y. Abe, H. Sasaki, M. Peres, K. Inoue, K. Murakami, and S. Kato. 
 "Power and Performance Analysis of GPU-Accelerated Systems", In 
 Proceedings of the 5th UESNIX Workshop on Power-Aware Computing and
@@ -82,6 +88,9 @@ S. Kato, J. Aumiller, and S. Brandt. "Zero-Copy I/O Processing for
 Low-Latency GPU Computing", In Proceedings of the 4th ACM/IEEE 
 International Conference on Cyber-Physical Systems (ICCPS'13), 2013.
 
+Y. Fujii, T. Azumi, N. Nishio, and S. Kato. "Exploring Microcontrollers
+in GPUs", In Proceedings of the 4th Asia-Pacific Workshop on Systems,
+(APSys'13), 2013.
 
 #####################################################################
 # Reclocking the GPU
@@ -110,12 +119,8 @@ program is finished. Then the clock remains at the maximum level.
 # Benchmarks and Applications
 #####################################################################
 
-Gdev currently supports CUDA Driver API, while many CUDA programs you
-may find today are written using CUDA Runtime API. As mentioned above,
-you can use Ocelot to translate CUDA Runtime API to CUDA Driver API,
-but we also provide some benchmarks and applications that are written
-using CUDA Driver API so that you can quickly start using Gdev.
-Try downloading the following:
+Today many CUDA programs are written using CUDA Runtime API. If you
+want to test CUDA Driver API, try the following benchmarks and apps.
 git@github.com:shinpei0208/gdev-app.git
 git@github.com:shinpei0208/gdev-bench.git
 
@@ -139,3 +144,4 @@ git@github.com:shinpei0208/gdev-bench.git
  Yusuke SUZUKI, Keio University
  Kaibo WANG, Ohio State University
  Hiroshi YAMADA, Tokyo University of Agriculture and Technology
+