Since LuxMark uses OpenCL, we can also use it to test both GPU and CPU performance—and even to compare performance across different processor types. Since OpenCL code is by nature parallelized and relies on a real-time compiler, it should adapt well to new instructions. For instance, Intel and AMD offer integrated client drivers for OpenCL on x86 processors, and they both claim to support AVX. The AMD APP driver even supports Bulldozer's and Piledriver's distinctive instructions, FMA4 and XOP.
We'll start with CPU-only results. These results come from the AMD APP driver for OpenCL, since it tends to be faster on both Intel and AMD CPUs, funnily enough.
Now we'll see how a Radeon HD 7950 performs when driven by each of these CPUs.
Finally, we can combine CPU and GPU computing power to see whether we can extract more performance with the two processor types both working on the same problem at once.
The FX-8350 decidedly outperforms the Core i5-3570K when asked to tackle the problem entirely by itself via the AMD APP ICD. Only the recent Intel CPUs with Hyper-Threading and four (or more) cores are faster. However, the Radeon is clearly more proficient at this job than any of the CPUs, and, like most of the processors, the FX-8350 is better off just feeding the Radeon data than trying to help with the computation.
The Cinebench benchmark is based on Maxon's Cinema 4D rendering engine. It's multithreaded and comes with a 64-bit executable. This test runs with just a single thread and then with as many threads as CPU cores (or threads, in CPUs with multiple hardware threads per core) are available.
Turns out the FX-8150 is no slouch in these rendering apps, and the FX-8350's solid gains over its predecessor allow it to place near the top of the charts, rivaling the Hyper-Threaded Intel quad cores.
STARS Euler3d computational fluid dynamics
Euler3D tackles the difficult problem of simulating fluid dynamics. Like MyriMatch, it tends to be very memory-bandwidth intensive. You can read more about it right here.
Performance in these two scientific computing workloads used to track together pretty closely, believe it or not, and appeared to be primarily limited by memory bandwidth. Over time, the performance results in these two workloads have diverged as CPU architectures have diverged.