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#raytracing

2 posts2 participants0 posts today

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

#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