From: Srinivas Jonnalagadda <srinivas.j@...>
Date: 2006-02-03T10:03:39+09:00
Subject: Re: neuroimage software - scientific computing and visualization

Acceleration of algorithms by moving the number-crunching parts to FPGAs 
has been well-utilized in the life sciences industry for a while now. 
Due to non-disclosure agreements, I cannot provide the details, but my 
company has been providing such solutions for the last couple of years.

Normally, once the board design is finalized, a suitable C 
implementation of the algorithm is used as the basis for a Verilog 
implementation to be burned into the FPGA. Typically, these FPGAs are 
mounted on PCI cards or USB devices.

A driver does the interface between the application in software and the 
FPGA, handling interrupt events, data handover, etc.

I would be interested in your work, unless you are building a commercial 
closed-source solution.

Best regards,

JS

ara.t.howard@noaa.gov wrote:
> On Fri, 3 Feb 2006, Joel VanderWerf wrote:
> 
>> Phil Tomson wrote:
>>> Here's an tantalizing idea that I'll throw out:  C is one thing and, 
>>> yes, it's
>>> fast.... but what if you could actually map some algorithm or math 
>>> operation to
>>> _hardware_ and thus get a large speed  advantage even over C?  I'm 
>>> working on
>>> something like this... details forthcoming.  The idea is very similar to
>>> Ruby::Inline.  It will allow seamless communication between your Ruby 
>>> program
>>> and an FPGA board acting as hardware accelerator (these boards are 
>>> available
>>> for less than $200 now).
>>
>> That would be very cool. Eventually, we're going to be porting a
>> wireless network stack to FPGA, and being able to still use Ruby would
>> be very nice.
>>
>> What kind of code goes inside your "inline" blocks?
> 
> this sounds insanely cool.  can you ping me offline phil?
> 
> -a
>