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@@ -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, @@ -38,12 +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: @@ -62,8 +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versions of GPGPU-Sim (3.2.0 to 4.1.0) included the [GPUWattch Energy model](http://gpgpu-sim.org/gpuwattch/) which has been replaced by AccelWattch version 1.0 in GPGPU-Sim version 4.2.0.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 @@ -108,21 +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, @@ -316,15 +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 |