1–10 of 44 posts
Feel free to ask questions about technical aspects of the GpuOwl implementation, about optimizations, tricks, efficient FFT implementation on GPUs etc. Or anything else.
[1] GpuOwl: https://github.com/preda/gpuowl [2] GIMPS: https://www.mersenne.org/
- Why use OpenCL when implementing GPU software
- Does it run on AMD or on Nvidia GPUs?
- How does the primality test implemented in GpuOwl work?
- How fast is it to test a Mersenne candidate?
- Why use FFTs? how large are the FFTs?
- What do you use for sin/cos?Indeed, I’m curious why you’ve used OpenCL. And what was the hardware/general setup used for finding the prime?
What was your motivation behind building this software?
1). What profiling tools do you use for GPU code?
2). Where one would start, in terms of learning resources, about coding using inline GPU assembler?
3). Do you verify GPU assembler generated by a compiler from C/C++ code, in terms of effectiveness? If so, which tools do you use for that?
4). Is SIMD on GPUs a thing?
5). What are the primary factors being taken into account by you (cache sizes, microoptimizations, etc.) when you write code for a tool like gpuowl/prpll? Which factor is the most important? Thanks!
Hi, I've got few questions: 1). What profiling tools do you use for GPU code? 2). Where one would start, in terms of learning resources, about coding using inline GPU assembler? 3). Do you verify GPU assembler generated by a compiler from C/C++ code, in terms of effectiveness? If so, which tools do you use for that? 4). Is SIMD on GPUs a thing? 5). What are the primary factors being taken into account by you (cache s…
Hi, I've got few questions: 1). What profiling tools do you use for GPU code? 2). Where one would start, in terms of learning resources, about coding using inline GPU assembler? 3). Do you verify GPU assembler generated by a compiler from C/C++ code, in terms of effectiveness? If so, which tools do you use for that? 4). Is SIMD on GPUs a thing? 5). What are the primary factors being taken into account by you (cache s…
2. I'm not aware of good learning resources. Explore existing such code, e.g. opencl miners tend to use asm. Read in amdgpu/ in LLVM. Disassemble code from OpenCL and read the ISA. Explore and experiment, but it's tedious. I would not recommend to jump into ISA initially. BTW AMD does have good GCN ISA docs available online, that is useful!
3. Yes I often read the compiled ISA, and over time I discover bugs and also better understand the ISA.
4. OpenCL is SIMD, and yes it matches the GPU HW.
5. most important is to reduce the number of registers used (#VGPRs), as that influences heavilly the occupancy of the kernel. Use fewer costly instructions such as FP64 mul/FMA. Sequential memory access, and in general reduce global memory access as it's very slow. Merge small kernels into one (keep the data in the kernel). Never spill VGPRs.
Wow, congrats! Indeed, I’m curious why you’ve used OpenCL. And what was the hardware/general setup used for finding the prime? What was your motivation behind building this software?
Motivation: a long time ago I had an AMD GPU and no way to run an LL test on it, so I decided to write my own. And I was hooked by the power of the GPU and the quest for ever more efficient, faster implem.
Hi, I've got few questions: 1). What profiling tools do you use for GPU code? 2). Where one would start, in terms of learning resources, about coding using inline GPU assembler? 3). Do you verify GPU assembler generated by a compiler from C/C++ code, in terms of effectiveness? If so, which tools do you use for that? 4). Is SIMD on GPUs a thing? 5). What are the primary factors being taken into account by you (cache s…
And another more general question: (6) gcc, clang, and nvcc have some OpenMP offloading capabilities which allow to compile code into binaries which can then run on GPUs. Is the code they produce through OpenMP anywhere close to what one gets directly with i.e. opencl?
I am contributing to GIMPS with 2 Radeon Pro VII cards. I'm wondering what will happen when ROCm stops supporting these GPUs.
Do you have any plans to keep them working with GPUOwl/Prpll when they are no longer supported by ROCm?
Second: I'm confused by something in your readme. It says:
> For Mersenne primes search, the PRP test is by far preferred over LL, such that LL is not used anymore for search.
But later notes that PRP is computationally nearly identical to LL. Was that sentence supposed to say TF and P-1 instead of PRP or am I misunderstanding something about the actual computational cost of PRP?