GeForce RTX 3080 FE GPGPU Compute Workstation Performance

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AIDA64 GPGPU Benchmark

AIDA64 is up next, it has a specific GPGPU benchmark that tests different GPGPU aspects of a GPU.  We have compared each of its results below, make sure to scroll down fully, there are 12 graphs on this page.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

This first graph tests GPU Memory read performance, which is the ability for the CPU to read into GPU memory.  The GeForce RTX 3080 FE is so much higher, 24GB/s because of PCI-Express 4.0 support.  It can read through the PCIe bus so much faster and so hence the speed difference here.  This is basically testing PCIe bandwidth.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

The same is true on this graph of Memory Write as it was with Memory Read.  We are basically just looking at the advantage of PCI-Express 4.0.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

Now, this graph is interesting, showing the Memory Copy performance.  The GeForce RTX 3080 FE can copy memory at about 647GB/s, which is faster than the other video cards.  It’s 77% faster than the GeForce RTX 2080 FE and 29% faster than the GeForce RTX 2080 Ti FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

Next up is Single-Precision FLOPS performance measured in GFLOPS.  GeForce RTX 3080 FE is way faster in single-precision performance.  It’s 176% faster than the GeForce RTX 2080 FE and 89% faster than the GeForce RTX 2080 Ti FE.  That’s like 2.5x times faster than the RTX 2080 FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

In this next graph, we are comparing Double-Precision FLOPS measured in GFLOPS.  GeForce RTX 3080 FE is 50% faster than the GeForce RTX 2080 FE and only 5% faster than the GeForce RTX 2080 Ti FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

Our next test in this benchmark is the 24-bit Integer IOPS measured in GIOPS.  The GeForce RTX 3080 FE is 52% faster than the GeForce RTX 2080 FE and 5% faster than the GeForce RTX 2080 Ti FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

The 32-bit Integer IOPS performance and results and percentages are exactly the same as 24-bit Integer IOPS.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

Now we are looking at 64-bit Integer IOPS.  GeForce RTX 3080 FE is 57% faster than GeForce RTX 2080 FE and 7% faster than GeForce RTX 2080 Ti FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

In this test, we are looking at AES-256 performance and it’s just through the roof on the GeForce RTX 3080 FE.  It’s a whopping 208% faster than the GeForce RTX 2080 FE and 110% faster than the GeForce RTX 2080 Ti FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

However, the SHA-1 Hash performance is only just as fast as the GeForce RTX 2080 Ti FE.  Which is still 72% faster than the GeForce RTX 2080 FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

The Single-Precision Julia test is 50% faster than GeForce RTX 2080 FE and 4% faster than the GeForce RTX 2080 Ti FE.

GeForce RTX 3080 FE GPGPU Compute Workstation Performance AIDA64 GPGPU Benchmark

The Double-Precision Mandel test on the RTX 3080 FE is 40% faster than the GeForce RTX 2080 FE and close to GeForce RTX 2080 Ti FE performance.

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Brent Justicehttps://www.thefpsreview.com
Former managing editor of GPUs at HardOCP for 18 years, Brent Justice has been reviewing computer components since the late 90s, educated in the art and method of the computer hardware review, he brings experience, knowledge, and hands-on testing with a gamer-oriented and hardware enthusiast perspective. You can follow him on Twitter - @Brent_Justice You can sub to his YouTube channel - Justice Gaming https://www.youtube.com/c/JusticeGamingChannel You can check out his computer builds on KIT - @BrentJustice https://kit.co/BrentJustice

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