Merge branch 'dev' into fix_different_latencies_to_same_ex_unit

1 files changed, 32 insertions, 28 deletions

diff --git a/README.md b/README.md
index 9f9f669..d0b14cd 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,8 @@
 Welcome to GPGPU-Sim, a cycle-level simulator modeling contemporary graphics
 processing units (GPUs) running GPU computing workloads written in CUDA or
 OpenCL. Also included in GPGPU-Sim is a performance visualization tool called
-AerialVision and a configurable and extensible energy model called GPUWattch.
-GPGPU-Sim and GPUWattch have been rigorously validated with performance and
+AerialVision and a configurable and extensible power model called AccelWattch.
+GPGPU-Sim and AccelWattch have been rigorously validated with performance and
 power measurements of real hardware GPUs.
 
 This version of GPGPU-Sim has been tested with a subset of CUDA version 4.2,
@@ -11,6 +11,11 @@ This version of GPGPU-Sim has been tested with a subset of CUDA version 4.2,
 Please see the copyright notice in the file COPYRIGHT distributed with this
 release in the same directory as this file.
 
+GPGPU-Sim 4.0 is compatible with Accel-Sim simulation framework. With the support 
+of Accel-Sim, GPGPU-Sim 4.0 can run NVIDIA SASS traces (trace-based simulation) 
+generated by NVIDIA's dynamic binary instrumentation tool (NVBit). For more information 
+about Accel-Sim, see [https://accel-sim.github.io/](https://accel-sim.github.io/)
+
 If you use GPGPU-Sim 4.0 in your research, please cite:
 
 Mahmoud Khairy, Zhesheng Shen, Tor M. Aamodt, Timothy G Rogers.
@@ -18,7 +23,7 @@ Accel-Sim: An Extensible Simulation Framework for Validated GPU Modeling.
 In proceedings of the 47th IEEE/ACM International Symposium on Computer Architecture (ISCA),
 May 29 - June 3, 2020.
 
-If you use CuDNN or PyTorch support, checkpointing or our new debugging tool for functional 
+If you use CuDNN or PyTorch support (execution-driven simulation), checkpointing or our new debugging tool for functional 
 simulation errors in GPGPU-Sim for your research, please cite:
 
 Jonathan Lew, Deval Shah, Suchita Pati, Shaylin Cattell, Mengchi Zhang, Amruth Sandhupatla, 
@@ -26,7 +31,6 @@ Christopher Ng, Negar Goli, Matthew D. Sinclair, Timothy G. Rogers, Tor M. Aamod
 Analyzing Machine Learning Workloads Using a Detailed GPU Simulator, arXiv:1811.08933,
 https://arxiv.org/abs/1811.08933
 
-
 If you use the Tensor Core model in GPGPU-Sim or GPGPU-Sim's CUTLASS Library 
 for your research please cite:
 
@@ -34,12 +38,11 @@ Md Aamir Raihan, Negar Goli, Tor Aamodt,
 Modeling Deep Learning Accelerator Enabled GPUs, arXiv:1811.08309, 
 https://arxiv.org/abs/1811.08309
 
-If you use the GPUWattch energy model in your research, please cite:
+If you use the AccelWattch power model in your research, please cite:
 
-Jingwen Leng, Tayler Hetherington, Ahmed ElTantawy, Syed Gilani, Nam Sung Kim,
-Tor M. Aamodt, Vijay Janapa Reddi, GPUWattch: Enabling Energy Optimizations in
-GPGPUs, In proceedings of the ACM/IEEE International Symposium on Computer
-Architecture (ISCA 2013), Tel-Aviv, Israel, June 23-27, 2013.
+Vijay Kandiah, Scott Peverelle, Mahmoud Khairy, Junrui Pan, Amogh Manjunath, Timothy G. Rogers, Tor M. Aamodt, and Nikos Hardavellas. 2021.
+AccelWattch: A Power Modeling Framework for Modern GPUs. In MICRO54: 54th Annual IEEE/ACM International Symposium on Microarchitecture
+(MICRO ’21), October 18–22, 2021, Virtual Event, Greece.
 
 If you use the support for CUDA dynamic parallelism in your research, please cite:
 
@@ -58,8 +61,8 @@ This file contains instructions on installing, building and running GPGPU-Sim.
 Detailed documentation on what GPGPU-Sim models, how to configure it, and a
 guide to the source code can be found here: <http://gpgpu-sim.org/manual/>.
 Instructions for building doxygen source code documentation are included below.
-Detailed documentation on GPUWattch including how to configure it and a guide
-to the source code can be found here: <http://gpgpu-sim.org/gpuwattch/>.
+
+Previous versions of GPGPU-Sim (3.2.0 to 4.1.0) included the [GPUWattch Energy model](http://gpgpu-sim.org/gpuwattch/) which has been replaced by AccelWattch version 1.0 in GPGPU-Sim version 4.2.0. AccelWattch supports modern GPUs and is validated against a NVIDIA Volta QV100 GPU. Detailed documentation on AccelWattch can be found here: [AccelWattch Overview](https://github.com/VijayKandiah/accel-sim-framework#accelwattch-overview) and [AccelWattch MICRO'21 Artifact Manual](https://github.com/VijayKandiah/accel-sim-framework/blob/release/AccelWattch.md).
 
 If you have questions, please sign up for the google groups page (see
 gpgpu-sim.org), but note that use of this simulator does not imply any level of
@@ -104,21 +107,20 @@ library (part of the CUDA toolkit). Code to interface with the CUDA Math
 library is contained in cuda-math.h, which also includes several structures
 derived from vector_types.h (one of the CUDA header files).
 
-## GPUWattch Energy Model
+## AccelWattch Power Model
 
-GPUWattch (introduced in GPGPU-Sim 3.2.0) was developed by researchers at the
-University of British Columbia, the University of Texas at Austin, and the
-University of Wisconsin-Madison. Contributors to GPUWattch include Tor
-Aamodt's research group at the University of British Columbia: Tayler
-Hetherington and Ahmed ElTantawy; Vijay Reddi's research group at the
-University of Texas at Austin: Jingwen Leng; and Nam Sung Kim's research group
-at the University of Wisconsin-Madison: Syed Gilani.
+AccelWattch (introduced in GPGPU-Sim 4.2.0) was developed by researchers at 
+Northwestern University, Purdue University, and the University of British Columbia. 
+Contributors to AccelWattch include Nikos Hardavellas's research group at Northwestern University: 
+Vijay Kandiah; Tor Aamodt's research group at the University of British Columbia: Scott Peverelle; 
+and Timothy Rogers's research group at Purdue University: Mahmoud Khairy, Junrui Pan, and Amogh Manjunath. 
 
-GPUWattch leverages McPAT, which was developed by Sheng Li et al. at the
+AccelWattch leverages McPAT, which was developed by Sheng Li et al. at the
 University of Notre Dame, Hewlett-Packard Labs, Seoul National University, and
-the University of California, San Diego. The paper can be found at
+the University of California, San Diego. The McPAT paper can be found at
 http://www.hpl.hp.com/research/mcpat/micro09.pdf.
 
+
 # INSTALLING, BUILDING and RUNNING GPGPU-Sim
 
 Assuming all dependencies required by GPGPU-Sim are installed on your system,
@@ -261,9 +263,10 @@ To clean the docs run
 The documentation resides at doc/doxygen/html.
 
 To run Pytorch applications with the simulator, install the modified Pytorch library as well by following instructions [here](https://github.com/gpgpu-sim/pytorch-gpgpu-sim).
+
 ## Step 3: Run
 
-Before we run, we need to make sure the application's executable file is dynamically linked to CUDA runtime library. This can be done during compilation of your program by introducing the nvcc flag "--cudart shared" in makefile (quotes should be excluded).
+Before we run, we need to make sure the application's executable file is dynamically linked to CUDA runtime library. This can be done during compilation of your program by introducing the nvcc flag "-lcudart" in makefile (quotes should be excluded).
 
 To confirm the same, type the follwoing command:
 
@@ -311,15 +314,16 @@ need to re-compile your application simply to run it on GPGPU-Sim.
 To revert back to running on the hardware, remove GPGPU-Sim from your
 LD_LIBRARY_PATH environment variable.
 
-The following GPGPU-Sim configuration options are used to enable GPUWattch
+The following GPGPU-Sim configuration options are used to enable AccelWattch
 
 	-power_simulation_enabled 1 (1=Enabled, 0=Not enabled)
-	-gpuwattch_xml_file <filename>.xml
-
+	-power_simulation_mode 0 (0=AccelWattch_SASS_SIM or AccelWattch_PTX_SIM, 1=AccelWattch_SASS_HW, 2=AccelWattch_SASS_HYBRID)
+	-accelwattch_xml_file <filename>.xml
 
-The GPUWattch XML configuration file name is set to gpuwattch.xml by default and
-currently only supplied for GTX480 (default=gpuwattch_gtx480.xml). Please refer to
-<http://gpgpu-sim.org/gpuwattch/> for more information.
+The AccelWattch XML configuration file name is set to accelwattch_sass_sim.xml by default and is
+currently provided for SM7_QV100, SM7_TITANV, SM75_RTX2060_S, and SM6_TITANX. 
+Note that all these AccelWattch XML configuration files are tuned only for SM7_QV100. Please refer to
+<https://github.com/VijayKandiah/accel-sim-framework#accelwattch-overview> for more information.
 
 Running OpenCL applications is identical to running CUDA applications. However,
 OpenCL applications need to communicate with the NVIDIA driver in order to