NDN-FIB

This repository contains collection of all the work related to the FPGA based FIB implementation for Name Data Network. Details of the work are available in the paper:

D. Saxena, Suyash Mahar, V. Raychoudhury, J. Cao
"Scalable, High-speed On-chip-based NDN Name Forwarding using FPGA".
To appear in International Conference on Distributed Computing and Networking (ICDCN), Bangalore, 2019.

Directory Structure

Analysis

Analysis directory contains a Jupyter notebook containing many of the analysis performed on the datasets. This is accompained by a C++ program, which implements stride analysis part of the Jupyter notebook. This is done to get better performance while processing large datasets.

BST implementation

The data structure used for performing lookup is implemented as a C++ script and associated functions. This allows construction of tree which can be used for analysis or for constructing memory contents for the FPGA.

Scripts

Scripts directory is collection of all the scripts ever used in the process of converting an FIB dataset to memory contents for FPGA.

Hardware Description

This directory contains the complete description of the FIB in Verilog HDL, it also includes pre-configured projects for single-issue and dual-issue implementation.

Performing simulation for using a dataset

Follow the following steps to convert a FIB dataset to memory contents for an FPGA:

1. Copy bst-impl/BST.cpp, all the scripts from scripts/ and the desired dataset into a new directory of your choice.
2. Use g++ BST.cpp -g --std=c++11 to compile the program used to generate the tree.
3. Use a.out <dataset name> <stride size> <1 for generating files that represent generated tree>
   e.g. ./a.out my_dataset.fib 4 1 to generate files for tree constructed using the dataset my_dataset.fib having stride size of 4, also it asks the program to write the representation files.
4. Use ./generateImplementationFiles.sh to generate memory files from the representative files generated from the previous step.
5. Rename the location for memory files in example Vivado project to use these files, also set the height of the tree appropiately.

Datasets

Dataset	sha256sum
Heavy Workload	ab7ca2e2bca76eaed07033c6418d0696c4bc173714ef0fe13f417a83934cc55a
Average Workload	cd31ac071e90a942a0abaec53d8d1a3c5d351a26ba8b1ffaf951bffa70867d8a
3.5M Dataset	c309c8fa5c6a888879c33e6b26ad753165af8b2ca3e75f2ecbefc54fbda7c913
0.5M dataset	8b6a0376a240ee4b3dc88f38a991f97626bdfbd4a8f2c9a95d48c9d27b0cc821
Combined without blacklist	2e3447d4eff85431c36951bdee1498330f44f3d30479c428ed7aac7c476ac5fa
Blacklist	21e77e8da0556048c5cf44076284daf98b71b388fb1615033003ffbade17ec19

Contributions

Feel free to file issues and submit pull requests - contributions are welcome.

Maintainer: Suyash Mahar
UG E&CE, IIT Roorkee
suyash12mahar@outlook.com