deathbyguitar
Power User
What's the ETA on seeing this in a public firmware?
I'm gonna guess maybe few weeks after FM3 5.0 makes it out of beta. I don't think Fractal ever has more than one beta running at a time.
What's the ETA on seeing this in a public firmware?
well...applying some deductive reasoning: last year, in late January, a Fractalaudio thread appeared called something like "you guys are in for a big treat" in which a it was revealed that some secrets of chugging had been discovered - Cygnus beta was released in mid February, and first went to full production in April. So by this logic, I'd guess we have a CygnusX2 beta by some time in February, and if it's anything like CygnusX1, we are in for another treat indeed!What's the ETA on seeing this in a public firmware?
I just got the Turbo and is so powerful that I can’t even imagine how to reach CPU limits (with a realistic preset).
With such achievements the Turbo will probably get even more power to understand what my wife says while I play…😱
I got there pretty quick (with Full Res) on some of mine.I just got the Turbo and is so powerful that I can’t even imagine how to reach CPU limits (with a realistic preset).
With such achievements the Turbo will probably get even more power to understand what my wife says while I play…😱
I've finally perfected the "Chase Nonlinear Feedback" (CNFB) method for the modeling of nonlinear networks. And it works amazingly well. Has the accuracy of high-order integration methods with less computational burden.
Can simulate diodes, triodes, pentodes, etc. Far less error-prone than other methods (like K-method or DK-method, etc.) as you don't need to enter large matrices or tables.
It works on the principle that nonlinear devices can be thought of as linear devices with nonlinear feedback. You compute the states of a linear network and apply nonlinear feedback to get the output. It's also inherently stable. If the analog version of the network is stable, the CNFB implementation is stable.
The plot below is a simple example. This is a single-sided diode clipper with "memory" (the memory being a capacitor across the diode). The dotted line uses classic nonlinear ODE techniques solving the network using Trapezoidal Rule integration. The dashed line uses the CNFB method. The results are virtually identical but the CNFB method executes in about 60% the time (12 operations per loop vs. 20). As the number of nodes in a network increases the computational advantage increases proportionally.
View attachment 93791
Here's a more complex example. This is a plot of a 6L6GC push-pull power amp into a reactive load (blue) compared to the same power amp simulated in SPICE (red). Doing this with conventional methods (nodal K, DK, WDF, etc.) induces major thinky-pain. I did this with the CNFB method in a couple hours.
View attachment 93826
Could be a revolution in nonlinear network modeling.
Cool stuff Mr Chase!I just finished porting the push-pull power amp algorithm to the Axe-Fx amp block and (after some debugging) it works. It doesn't sound markedly different but it sounds slightly more open. Measures slightly different too. But we're talking tenths of a dB so...
Right now it's using more CPU than the previous version. I'll need to spend some time doing optimization.
Potentially 40% of the CPU load of an amp block saved - not 40% of total capacity. Still, amp blocks use a fair bit of CPU, so savings may be enough to make a nice dent....Potentially 40% more cpu for free!? I wonder if this will work for the effects at some level as well as the modeling? Seems it would be a major re-write of what we have, but Cliff has done this in the past, which blows my mind!
Yeah. Drive blocks use a lot too (on the III, don't know about other devices).Potentially 40% of the CPU load of an amp block saved - not 40% of total capacity. Still, amp blocks use a fair bit of CPU, so savings may be enough to make a nice dent....
That also assumes the new method can be used for 100% of the tasks running in the amp CPU, and all of them have the same 40% saving.Potentially 40% of the CPU load of an amp block saved - not 40% of total capacity. Still, amp blocks use a fair bit of CPU, so savings may be enough to make a nice dent....
I thought the new method was inherently more efficient, and by a decent amount. Just curious why you need to optimize just to get back to par.I just finished porting the push-pull power amp algorithm to the Axe-Fx amp block and (after some debugging) it works. It doesn't sound markedly different but it sounds slightly more open. Measures slightly different too. But we're talking tenths of a dB so...
Right now it's using more CPU than the previous version. I'll need to spend some time doing optimization.
I have 8 more pages of posts to read them all, and maybe there will be more explanation that Cliff posts, but this was also my takeaway - it must be pretty awesome if he took the time to excitedly inform us.If cliff is excited enough to post about it, it cant be bad.
Twin TurboMaybe this makes the Mark I/II effectively a Turbo and the Turbo becomers Turbo-er