- in order to find the best configuration based on its performance
- other tasks
-[WebPPL: ](http://webppl.org/) probabilistic programming for the web
- Probabilistic Graphical Models
In order to map the hardware architecture to an input dataflow program or computation graph, I modeled the hardware and software models as probabilistic graphical model, and used probabilistic programming to infer the best hardware architecture choices that will optimize the speed, energy and cost of the system.
I used [WebPPL](http://dippl.org/chapters/02-webppl.html) a probabilistic programming language in javascript. I model the variables I want to infer as if they come from different types of distributions that integrate our priors in them. In the following example I am using markov chain monte carlo as an inference method.
Until now I have a dummy computation model. Next steps would be to get a complex computational graph and for each part infer the best hardware architecture for it. Moreover, if the computation graph changes through time one can also alter the hardware architecture to respond to these changes.
### Applications
### Applications
- The idea is to find an application that needs reconfiguration white running, examples:
- The idea is to find an application that needs reconfiguration white running, examples:
- Gamalon probabilistic programming
- Gamalon probabilistic programming
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#### Probabilistic Programming
-[Gamalon](https://gamalon.com/)
- Using Dice pieces to do **inference**
- in order to find the best configuration based on its performance
- other tasks
-[WebPPL: ](http://webppl.org/) probabilistic programming for the web