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  • Hey all, just changed over the backend after 15 years I figured time to give it a bit of an update, its probably gonna be a bit weird for most of you and i am sure there is a few bugs to work out but it should kinda work the same as before... hopefully :)

Just so you know...

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Jannard

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REDCINE is not finished. In fact, it has just begun. There are many more pleasant surprises coming for new RED ONE formats, all of which will be supported in REDCINE. There are still a few output options in the works as well. Think of REDCINE as being the brother to the RED ONE. Always being improved and never finished...

Jim
 
ok, this has been bugging me...is REDCINE pronounced "red-seen" or "red-sin-ay"?

thanks for the near-daily dose of miracles...
 
Thanks Jim for giving us this awesome product!
It never crashed on me. And that's pretty impressive for a first beta release!
Kudos to the whole team!
 
Any chance Redcine will grow by taking advantage of the possibilities described in this article? http://news.bbc.co.uk/2/hi/technology/7079701.stm

That article talks about using the graphics processor (GPU) instead of or in addition to the main processor CPU. Redcine already does this; that's why it doesn't work on systems unless they have a newer graphics card with a programmable GPU (Nvidia, etc.).
 
That article talks about using the graphics processor (GPU) instead of or in addition to the main processor CPU. Redcine already does this; that's why it doesn't work on systems unless they have a newer graphics card with a programmable GPU (Nvidia, etc.).

Actually it talks about using ONLY graphic card GPUs to do repetitive work (like conforming or rendering?) on an almost supercomputer scale. So, multiple cards on a standard computer being used simultaneously?

To wit: But the scientists in question are not using the cards to appreciate the detail in PC games such as The Witcher. Instead they are using them as cheap sources of supercomputer-class processing power.

"They give a phenomenal bang for the buck," said Mike Giles, professor of scientific computing at the University of Oxford.

and.....

Prof Giles, who is using graphics processors to do financial modelling, said the chips were very good at doing the same thing many different times.

By contrast the Intel or AMD chips inside a typical desktop machine were good at doing many different things at the same time.

Graphics cards had far more processing cores - which execute program instructions - than Intel or AMD chips, said Prof Giles, adding that each one of the cores could do one run of the same simple task.

The financial models that Prof Giles is running test the same algorithm on each core but each one gets different random numbers as input.

With the latest graphics processors having more than 100 processing cores that can add up to a lot of number crunching.

Even better, he said, each of those processing cores was as good at crunching numbers as a single Intel or AMD microprocessor.

"Each core is logically very simple but its floating point capability is the same as an Intel chip," said Prof Giles.

Developments in methods of writing code to handle the processing was also making graphics processors much more attractive, he said.

"In the early days you could only use graphics cards for graphics," said Prof Giles.

In particular, he said, graphics card maker Nvidia had released software tools called Cuda (Compute Unified Device Architecture) that made it much easier to write code.

"For a while there were only hard-to-use shader languages," said Prof Giles, "Cuda is a much more usable development environment."
 
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