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So how do these stack up against running that same workload (simulations) on a powerful GPU? Often a sim requires running the same operation over thousands of d
by wallacoloo 5y ago
So how do these stack up against running that same workload (simulations) on a powerful GPU? Often a sim requires running the same operation over thousands of different cells: it seems really suited to the “warp” style of parallelism, where all cores in a set run the same instruction in lockstep. Or SIMD, but that’s usually a bit more effort to port. LLVM has a spirv backend these days, so does POWER actually make sense for these workloads outside of places where it’s difficult to port your codebase?
- ChuckMcM 5y agoGenerally it depends on the working set. Massively parallel architectures with shared visibility into a coherent memory space can often more efficiently compute volumetric problems. Doing the same problems on GPUs involve a lot of data shuffling and you end up on the wrong side of Amdahl's law.