Qualcomm investigating Adreno X2 support for Folding@Home

[Ncard00]

Qualcomm is now reviewing the technical feasibility of bringing the necessary compute stack to the Snapdragon X2 for FAH.

They are aware of the GROMACS requirements and are looking at how to implement the precision needed for molecular dynamics.

[toTOW]

GROMACS on GPUs sucks It's still too dependent on the CPU.

And it will already run on ARM CPUs (although big.LITTLE shit is always a pain).

[Ncard00]

GROMACS on GPUs sucks It's still too dependent on the CPU.

And it will already run on ARM CPUs (although big.LITTLE shit is always a pain).

Update: Breakthrough in Adreno GPU Compute Stability

Since my last post, I have moved from theoretical feasibility to verified results. I have successfully bypassed current software limitations and executed large-scale scientific compute tasks natively on the Adreno X1-45 iGPU (Snapdragon X Elite) using OpenCL 3.0.

Contrary to the typical "mobile GPU" skepticism, the Adreno X1 platform demonstrates desktop-class stability and performance in long-term compute scenarios:

Proof of Performance: I successfully ran PrimeGrid GFN-22 on the Adreno iGPU, completing tasks in 33 hours compared to a 14-day estimate on the Oryon CPU.

GPU Utilization: Maintained 100% sustained load on the Adreno core without driver crashes or TDR issues, proving the compute stack is ready for more than just mobile tasks.

Benchmarking: GFN-16 tasks completed at a stable 04:36 minutes.

While GROMACS is indeed CPU-dependent, my results show that the Adreno iGPU can handle massive mathematical workloads independently when properly addressed via OpenCL.

I have also identified the presence of the Qualcomm Native Neural Network (QNN) interface (QnnHtp.dll) and the Hexagon Tensor Processor (HTP) driver, which opens up for potentially massive efficiency gains in molecular dynamics if bridged correctly via DirectML or QNN.

The hardware is no longer the bottleneck—the whitelist and official support are all that remain.

[muziqaz]

Please demonstrate the stability of the software and hardware on openmm. It has it's own benchmarking suite, which can be used to compare performance wise to other hardware as well as test the computational stability.
Other distributed computing projects' stability is irrelevant to FAH

[Ncard00]

Please demonstrate the stability of the software and hardware on openmm. It has it's own benchmarking suite, which can be used to compare performance wise to other hardware as well as test the computational stability.
Other distributed computing projects' stability is irrelevant to FAH

The focus on OpenMM benchmarks at this stage is a distraction from the core issue.

I am currently testing the Snapdragon X2 Elite Extreme (X2-90) with 80+ TFLOPS of theoretical NPU/GPU compute power, but the hardware is completely invisible to the FAH client because it is not whitelisted.

Running a complex Python-based OpenMM suite just to "prove" stability is unnecessary when the hardware is already proven stable under 100% load in other OpenCL environments.

The bottleneck isn't the hardware or its stability; it's the missing official bridge between the Adreno X2 compute stack and the FAH whitelist.

Qualcomm has the silicon ready for "Green Crunching" on a massive scale, but as long as the hardware IDs aren't mapped, this remains a waste of scientific potential.

We should stop asking users to perform engineer-level debugging and start demanding that the vendors provide the basic software-to-hardware mapping required for scientific work.

[muziqaz]

No, running OpenMM will show everyone:
If SD GPUs can run opencl/openmm code.
How it compares with normal GPUs performance wise
If Qualcomm drivers are capable of stable operations under OpenMM workloads.

You see, we, as in FAH, absolutely do not care if hardware is capable of some random workload which has nothing to do with OpenMM. If you want Qualcomm stuff taken seriously by FAH devs, run OpenMM benchmark suite and show us the results.
You will not going to get FAH support for Qualcomm GPUs without above as a minimum. It was explained quite a few times why, as well.
If you want a niche hardware to be even considered to be supported, you need to do the extra work. FAH is not a simple 2+2 algorithm, it is complex simulation, so if you want progress, prove it can run openmm.
And stop with the PR lingo, there is no need for this here