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#raytracing

1 post1 participant0 posts today

It's funny how simple and fast a basic raytracer can be.

I remember in my first year of IT school (2007-2008) when we had to implement one on CPU, and we had to wait several minutes for one picture to be rendered.

Of course this one is still very basic, but hey it's in real time baby

Continued thread

I'm still playing with this scene. In the past week I've added the plate, and this potion, and reoriented the picture to serve as a manual cover. In this process I'm getting more reaquainted with #povray #raytracing but I still ought to make the leap to Blender at some point.

I used to pick the time as the 3rd dimension to debug the 3D gradient noise, but unless you're into cloudy atmospheres, it's much better to display it on a 3D sphere.

Note: partial derivative magnitude on the right side if you wonder

Examining #RDNA4's out-of-order memory accesses in detail, and investigating with testing
#RDNA 4's memory subsystem enhancements are exciting and improve performance across a variety of workloads. #AMD specifically calls out benefits in #raytracing. But RDNA 4's scheme for handling memory dependencies isn't fundamentally different from that of #GCN many years ago. RDNA 4’s makes the most significant change to AMD’s #GPU memory subsystem since RDNA launched in 2019.
chipsandcheese.com/p/rdna-4s-o

Chips and Cheese · RDNA 4's "Out-of-Order" Memory AccessesBy Chester Lam

#raytracing folks, what do you think of next event estimation vs simple MIS (generate either brdf sample or light sample, use total probability in MC estimator)?

My former student insists on NEE, but it has so many special cases that I doubt it's a good idea pedagogically.

#FluidX3D #CFD v3.2 is out! I've implemented the much requested #GPU summation for object force/torque; it's ~20x faster than #CPU #multithreading. 🖖😋
Horizontal sum in #OpenCL was a nice exercise - first local memory reduction and then hardware-supported atomic floating-point add in VRAM, in a single-stage kernel. Hammering atomics isn't too bad as each of the ~10-340 workgroups dispatched at a time does only a single atomic add.
Also improved volumetric #raytracing!
github.com/ProjectPhysX/FluidX