Elevate the level of your hardware design from instances to generators! This bootcamp teaches you Chisel, a Berkeley hardware construction DSL written in Scala. It teaches you Scala along the way, and it frames the learning of Chisel on the idea of hardware generators.
- Why hardware designs are better expressed as generators, not instances
- Basics and some advanced features of Scala, a modern programming language
- Basics and some advanced features of Chisel, a hardware description language embedded in Scala
- How to write unit tests for Chisel designs
- familiarity with Verilog, VHDL, or at the very least, hardware design in general
- programming experience in a modern language, be it in Python, Java, C++, etc.
- an earnest desire to learn something new
The bootcamp is divided into modules, which are further subdivided. This README serves as Module 0, an introduction and motivation to learning the material contained within. Module 1 gives a quick introduction to Scala. It teaches you enough to start writing Chisel, but many more Scala concepts are taught along the way. Chisel is introduced in Module 2, starting with a hardware example and breaking it down. The rest of Module 2 covers combinational and sequential logic, and software and hardware control flow. Module 3 takes advantages of Scala's high-level programming language features to teach writing Chisel hardware generators. By the end, you will be able to read and understand most of the Chisel code base and Rocket Chip code. It does not yet cover SBT, FIRRTL, Rocket Chip usage, or ChiselDSP.
All hardware description languages support writing single instances. However, writing instances is tedious. Why make the same mistakes writing a slightly modified version of something somebody else has likely already designed? Verilog supports limited parameterization, such as bitwidths and generate statements, but this only gets you so far. If we can't write a Verilog generator, we need to write a new instance, thus doubling our code size. As a better option, we should write one program that generates both hardware instances, which would reduce our code size and make tedious things easier. These programs are called generators.
Ideally, we want our generators to be (1) composable, (2) powerful, and (3) enable fine-grain control over the generated design. Error checking is necessary to make sure a composition is legal; without it, debugging is difficult. This requires a generator language to understand the semantics of the design (to know what’s legal and what’s not). Also, the generator should not be overly verbose! We want the generator program to concisely express many different designs, without rewriting it in if statements for each instance. Finally, it should be a zero-cost abstraction. Hardware design performance is very sensitive to small changes, and because of that, you need to be able to exactly specify the microarchitecture. Generators are very different than high-level-synthesis (HLS).
The benefits of Chisel are in how you use it, not in the language itself. If you decide to write instances instead of generators, you will not see any advantages of Chisel over Verilog. But, if you take the time to learn how to write generators, then the power of Chisel will become apparent and you will realize you can never go back to writing Verilog. Learning to write generators is difficult, but we hope this tutorial will pave the way for you to become a better hardware designer, programmer, and thinker!
Run the instructions below for your particular situation. Note that we include a custom javascript file for Jupyter, so if you already have Jupyter installed, you still need to install the custom.js file.
First install Jupyter Scala.
Dependencies: openssh-client, openjdk-8-jre, openjdk-8-jdk (-headless OK for both), ca-certificates-java
First, use pip3 to install jupyter (or pip for python 2): http://jupyter.org/install.html
pip3 install --upgrade pip
pip3 install jupyter
Then, clone this repo and run the installation script: https://github.com/alexarchambault/jupyter-scala
git clone https://github.com/jupyter-scala/jupyter-scala.git
cd jupyter-scala && ./jupyter-scala
Now clone this repo and install the customization script. If you already have one, append this script to it.
git clone https://github.com/ucb-bar/generator-bootcamp.git
cd generator-bootcamp
mkdir -p ~/.jupyter/custom
cp source/custom.js ~/.jupyter/custom/custom.js
And to start the bootcamp on your local machine:
jupyter notebook
Be sure java is installed (ideally java 8).
If you type java into a command prompt and it says command not found, you need to install java.
Download Coursier: https://git.io/vgvpD
Go to download folder, where "coursier" (file) is
java -noverify -jar coursier launch -r sonatype:releases -r sonatype:snapshots -i ammonite -I ammonite:org.jupyter-scala:ammonite-runtime_2.11.11:0.8.3-1 -I ammonite:org.jupyter-scala:scala-api_2.11.11:0.4.2 org.jupyter-scala:scala-cli_2.11.11:0.4.2 -- --id scala --name "Scala"
Download this repository as a zip file (or use a Windows git client) and unpack it.
Install the customization script by moving generator-bootcamp/source/custom.js to ~/.jupyter/custom/custom.js.
If you already have a custom.js file, append this script to it.
If you don't know or don't have access to Cadence AWS, skip this section.
Navigate to your working directory, which is probably your home directory.
Then run the following commands.
The default shell is c-shell, but if you switch to bash, source jupyter_sh instead of jupyter_csh.
source /craft/tools/jupyter/jupyter_csh
The default browser, Konqueror, won't work with Jupyter. Launch Firefox and set it as your default browser when it asks.
/craft/cdns_sw_inst/firefox/45.3.0esr/firefox
Clone the repo and launch Jupyter. If it asks for a token, copy and paste the to login with a token URL seen in the terminal. Future launches will be happy for a while.
git clone /craft/tools/chisel/generator-bootcamp.git
cd generator-bootcamp
cp /craft/tools/jupyter/jupyter_support/rocket-dsp-utils-assembly-1.0.jar ../
jupyter notebook
If you don't know what the Cadence Chamber is, skip this section.
Navigate to your work directory, likely /projects/craft_flow/work/<username>/.
Then run the following commands.
Note that /proj/ is an alias to /projects/.
If you are in bash, source jupyter_sh instead of jupyter_csh.
source /proj/craft_flow/tools/jupyter/jupyter_csh
git clone /proj/craft_flow/source/chisel/generator-bootcamp
cd generator-bootcamp
jupyter notebook
- Stevo Bailey (stevo@berkeley.edu)
- Adam Izraelevitz (adamiz@berkeley.edu)
- Richard Lin (richard.lin@berkeley.edu)
- Chick Markley (chick@berkeley.edu)
- Paul Rigge(rigge@berkeley.edu)
- Edward Wang (edwardw@berkeley.edu)