During my final year at Indian Institute of Technology Madras, I worked on accelerating a decoder for Polar Codes. My project was titled ‘A GPU implementation of Belief Propagation Decoder for Polar Codes’. I used GPUs to accelerate the decoding process for Polar Codes.
Polar Codes are a class of capacity achieving codes for any Binary-input Discrete Memoryless Channel (B-DMC). These are based on the concept of channel polarization which suggests that given N-independent copies of a channel, we can synthesize another set of N-channels, that show a polarization effect in the sense that as N grows large, the channels tend to become either completely noisy or completely noise-free, with the noise-free channels approaching the capacity. Channel polarization suggests that we transmit information with rate 1 over these noise-free channels, while fixing the symbols over the noisy-channels to values known to both the sender and receiver.
I implemented the Belief Propagation decoder for Polar Codes using GPUs and observed a good throughput rate. I submitted an extended abstract at Asilomar Conference on Signals, Systems and Computers, 2012. It was accepted and I was invited to present my results at the conference which was held at Asilomar Conference Grounds, Pacific Grove, California from November 4th to 7th.
Firstly, the place was really awesome. It was along the coast and the conference housing had a great view of the ocean. The lodging was like one of those medieval-style architecture.
The place itself was really beautiful. The weather was pleasant. And I have been longing for a good beach for quite some time. My professor joined me for the conference. After checking into the hotel room, the first thing he said, “Come on, let’s go to the beach!”
It was a great place to watch sunset all the way.
This was my paper
I might have been one of the youngest persons to present at this conference. And these are my presentation slides. My paper would soon be published in the IEEE proceedings.