Reason: A Shell for Research Papers
- Did I ever read this paper?
- Which OSDI 2021 papers did I read?
- Which ones have the word 'Distributed' in their title?
- How many papers in 2020 were co-authored by Professor Byung-Gon Chun?
Well, ask reason.
How it works
For actual demos, refer to the wiki.
Filter and list papers
$ reason
>> # Show all papers.
>> ls
+----------------------------------------------------------+----------------+---------+------+
| title | first author | venue | year |
+============================================================================================+
| Shadowtutor: Distributed Partial Distillation for Mobile | Jae-Won Chung | ICPP | 2020 |
| Video DNN Inference | | | |
|----------------------------------------------------------+----------------+---------+------|
| Efficient Memory Disaggregation with Infiniswap | Juncheng Gu | NSDI | 2017 |
|----------------------------------------------------------+----------------+---------+------|
| Refurbish Your Training Data: Reusing Partially | Gyewon Lee | ATC | 2021 |
| Augmented Samples for Faster Deep Neural Network | | | |
| Training | | | |
|----------------------------------------------------------+----------------+---------+------|
| Finding Consensus Bugs in Etherium via Multi-transaction | Youngseok Yang | OSDI | 2021 |
| Differential Fuzzing | | | |
|----------------------------------------------------------+----------------+---------+------|
| Tiresias: A GPU Cluster Manager for Distributed Deep | Juncheng Gu | NSDI | 2019 |
| Learning | | | |
|----------------------------------------------------------+----------------+---------+------|
| Nimble: Lightweight and Parallel GPU Task Scheduling for | Woosuk Kwon | NeurIPS | 2020 |
| Deep Learning | | | |
+----------------------------------------------------------+----------------+---------+------+
>> # Filter by 'title'.
>> ls 'Deep Learning'
+------------------------------------------------------------+--------------+---------+------+
| title | first author | venue | year |
+============================================================================================+
| Tiresias: A GPU Cluster Manager for Distributed Deep | Juncheng Gu | NSDI | 2019 |
| Learning | | | |
|------------------------------------------------------------+--------------+---------+------|
| Nimble: Lightweight and Parallel GPU Task Scheduling for | Woosuk Kwon | NeurIPS | 2020 |
| Deep Learning | | | |
+------------------------------------------------------------+--------------+---------+------+
>> # You may set default filters with `cd`.
>> # BTW, `cd .`, `cd ..`, `cd -`, and `cd` are supported, too.
>> cd 'Deep Learning'
>> pwd
title matches 'Deep Learning'
>> # Default filter are automatically applied.
>> # Infiniswap (NSDI'17) is not shown, because its title doesn't match 'Deep Learning'.
>> ls at NSDI
+------------------------------------------------------------+--------------+---------+------+
| title | first author | venue | year |
+============================================================================================+
| Tiresias: A GPU Cluster Manager for Distributed Deep | Juncheng Gu | NSDI | 2019 |
| Learning | | | |
+------------------------------------------------------------+--------------+---------+------+
>> # Delete Tiresias.
>> ls at NSDI | rm
Removed 1 paper.
Import new papers
>> # Import directly from arXiv and USENIX. This will also download paper PDFs.
>> curl https://arxiv.org/abs/2105.11367
+--------------------------------------------------------+--------------+-------+------+
| title | first author | venue | year |
+======================================================================================+
| FedScale: Benchmarking Model and System Performance of | Fan Lai | arXiv | 2021 |
| Federated Learning | | | |
+--------------------------------------------------------+--------------+-------+------+
>> curl https://www.usenix.org/conference/nsdi21/presentation/you
+------------------------------------------+--------------+-------+------+
| title | first author | venue | year |
+========================================================================+
| Ship Compute or Ship Data? Why Not Both? | Jie You | NSDI | 2021 |
+------------------------------------------+--------------+-------+------+
>> # Modify paper metadata.
>> ls ship | set as Kayak
>> # Or, import manually.
>> touch 'Batch Normalization: Accelerating Deep Network Training by Reducing Internal
Covariate Shift' by 'Sergey Ioffe, Christian Szegedy' at ICML in 2015 as BN @ BatchNorm.pdf
+--------------------------------------------------------------+--------------+-------+------+
| title | first author | venue | year |
+============================================================================================+
| Batch Normalization: Accelerating Deep Network Training by | Sergey Ioffe | ICML | 2015 |
| Reducing Internal Covariate Shift | | | |
+--------------------------------------------------------------+--------------+-------+------+
Read, take notes, and create books!
>> # Open with a PDF viewer (`open`) and edit markdown notes with your editor (`ed`).
>> ls 'Why Not Both' | open | ed
+------------------------------------------+--------------+-------+------+
| title | first author | venue | year |
+========================================================================+
| Ship Compute or Ship Data? Why Not Both? | Jie You | NSDI | 2021 |
+------------------------------------------+--------------+-------+------+
>> # Format your markdown notes into an HTML book, and open it in your browser.
>> ls 'Deep Learning' | printf
+------------------------------------------------------------+--------------+---------+------+
| title | first author | venue | year |
+============================================================================================+
| Tiresias: A GPU Cluster Manager for Distributed Deep | Juncheng Gu | NSDI | 2019 |
| Learning | | | |
|------------------------------------------------------------+--------------+---------+------|
| Nimble: Lightweight and Parallel GPU Task Scheduling for | Woosuk Kwon | NeurIPS | 2020 |
| Deep Learning | | | |
+------------------------------------------------------------+--------------+---------+------+
Commands
Invoking reason will start a new command prompt. It accepts unix-like commands that instead work on research papers in your paperbase.
Works now:
lsfilters and prints papers in table format. Default columns are title, first author(by1), venue(at), and year(in).cdadds an AND filter to the default set of filters (which is empty upon startup).pwdshows the current default filter set bycd.touchcreates a new entry in your paperbase.curlimports papers from the web, e.g. arXiv or usenix.org. It also downloads paper PDFs if available.rmremoves entries from your paperbase.setsets attributes of papers.printfcreates an HTML page of your notes usingmdbook.openopens the paper with Zathura.edopens your editor (defaulting tovimbut abiding by$EDITOR), in which you can edit your notes.manplus a command will print documentation for that command.exitor Ctrl-d quitsreason.
Not yet, but hopefully soon:
grepreturns a list of papers whose notes contain the query string that you specify.sortsorts papers by given columns.statprints the metadata and notes of papers.topprints out a summary of your paperbase.syncstores the paper metadata state to disk.
Configuration
The configuration file is kept at ~/.config/reason/config.toml. If not present, reason will generate one populated with default settings.
For more information, open reason and run man config.
Todo
Shell-like experience
- Run commands.
- Support pipes between commands. A command passes a list of papers to the next command.
- GNU Readline features (up arrow, down arrow, Ctrl-A, Ctrl-E, Ctrl-L, etc).
- Allow scripting, e.g.
reason import.rewill runimport.reline-by-line.
Configuration
- Allowing configuration.
- Tweaking table appearance.
- Regex-related (?)
Paper metadata
- Support labels (with keyword 'is' and 'not').
Commands
-
ls -
cd -
pwd -
touch -
curl -
exit -
rm -
grep -
sort -
set -
stat -
printf -
open -
ed -
top -
sync -
man -
exit
640 Dec 29, 2022
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31 Jul 27, 2022
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302 Jan 4, 2023
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21 Mar 26, 2023
256 Dec 14, 2022
22.5k Jan 8, 2023
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