Commit e67ce926 authored by Sabyasachi Mondal's avatar Sabyasachi Mondal
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parent 94adbd08
......@@ -12,7 +12,8 @@ CPUs are known for their general purpose use, the same GPUs can power all kinds
In this case we are going to use the FPGA to implement a processing unit in hardware from High Level C code that will be able to compute
1. The weight matrix of a neural network
2. Do a liner search
2. Do a liner search
compare how CPU performs in comparision to our FPGA hardware that is exactly wired up to work on the kind of data we expect to provide as input.
......@@ -30,8 +31,16 @@ Next we implement the same algorithm in our python code that will obviously run
Then finally we can check the runtime and reach a conclusion on which is faster and why.
# Tasks
The Tasks adn time plan are recorded below:
The Tasks and maximum estimated time:
0. Problem statement and solution Plan brainstorming : 12 hrs
1. Pseudo code and solution adjustment : 3 hrs
2. Vivado study of other solutions, available tools, code and hardware correlation : 12 hrs
3. Writting the code in Vivado : 3 hrs
4. Implementing code and checking hardware features and making final adjustments : 5 hrs
5. Bitstream generation python code for overlay : 2 hrs
6. Implementing same algorithm in python CPU : 3 hrs
# Resources and Future questions
TO be added later
To be added later
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