Getting started

This is a short description. We refer you to the full documentation that can be found here:

https://ibm.github.io/microprobe/

IBM users can refer to the following extended documentation:

https://pages.github.ibm.com/MicroProbe/microprobe_private/

Required commands

git
python (3.7, 3.8, 3.9)
virtualenv: https://virtualenv.pypa.io/en/stable/

We are assuming a bash environment throughout the process. You might try to use other shell, although some commands might need to be modified accordingly. Execute the following commands the first time:

git clone --recursive git@github.com:IBM/microprobe.git INSTALLDIRECTORY/microprobe
cd INSTALLDIRECTORY/microprobe
bootstrap_environment.sh

Hopefully, the installation is complete. Otherwise, report the error to the development team. The commands above did the following: create a virtual python environment to avoid any dependency issues (which we found quite often...) and activate it. Then, we have checked out the repository and all of its submodules. Finally, we installed the required dependencies.

Using Microprobe

Assuming that all the variables above are set in your environment, you just need to execute the following command to start using Microprobe.

cd INSTALLDIRECTORY
source activate_microprobe

You will see that you command prompt changes. You should be able to execute the Microprobe related commands. This should be the only command you need to execute before using Microprobe related commands.

Updating Microprobe

Since we are in development mode, you just need to go to INSTALLDIRECTORY/microprobe and execute the following command:

git pull --update --recurse-submodules
find . -name \.*.cache -delete
find . -name \.*.lock -delete

Basically, we are pulling the latest copy of the repository and the submodules, and cleaning up any cached files.

Contributing to Microprobe

See CONTRIBUTING for policies on pull-requests to this repo.

Microprobe

Microprobe is a productive microbenchmark generation framework that an user can adapt towards exercising a complex multi-core, multi-threaded computing system in a variety of redundant ways for answering a range of questions related to energy and performance.

The growth in complexity of microprocessor systems today --composed of multi-core, multi-threaded processors with multi-level cache hierarchies and giga-bytes of memory--, hardens the pre-silicon system modeling and the post-silicon system characterizations. We believe that microbenchmarks, generated with particular objectives in mind, hold the key to obtaining accurate characterizations of microprocessor systems. Specially crafted microbenchmarks may be run on simulators (pre-silicon stage) or real machines (post-silicon stage) to help understand, diagnose and fix deficiencies systematically. However, manual generation of such "stress-marks" is tedious, and requires intimate knowledge of the underlying microarchitecture pipeline semantics. Automated microbenchmark generation is therefore crucial in this regard. Microprobe is developed to fulfill that need.

Key features

The automated generation facility must maximize the productivity of the end-user, allowing the generation of different classes of microbenchmarks that are useful in answering a range of different (unknown/future) questions. Therefore, we develop Microprobe with the following features in mind:

Adaptive and flexible. We design the microbenchmark synthesizer of Microprobe to work in a compiler-like fashion, i.e. applying a set of passes to a internal representation of the microbenchmark. This allows the users to adapt the microbenchmark generation process to their needs, providing the flexibility and the extensibility required.
Microarchitecture semantics aware. Microprobe includes low-level information of the target microarchitectures. This information is crucial to assist the generation of microarchitecture aware microbenchmarks, allowing the definition of microbenchmark generation policies based on them. It provides a white-box solution to the users to define microbenchmarks with very specific microarchitecture properties, avoiding the need to master every detail of the complex underlying architectures.
Integrated design space exploration (DSE). Design space explorations have become mandatory to understand the performance of computer architectures due to their increase in complexity. In addition, DSE are required to find microbenchmarks that fulfill a set of dynamic properties that cannot be ensured statically (during code generation). DSE support is therefore a basic functionality that any productive microbenchmark generation framework should have. Microprobe provides generic DSE support to be able to implement different customizable search strategies within the design space defined by the user (feature not yet released)