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Propose parallel path #4
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I think the other thing missing from the background information is the relative differences in workload expected on different systems. e.g. how much should someone be able to do on a laptop?
moves the code base into a position that will be easier to parallelize | ||
through one of the GPU libraries | ||
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### 3) CyCL |
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### 3) CyCL | |
### 3) SYCL |
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And throughout the following paragraphs.
3. [OpenMP](https://openmp.org) | ||
4. [CUDA](https://developer.nvidia.com/cuda-zone) | ||
5. [OpenCL](https://www.khronos.org/opencl/) | ||
6. [CyCL](https://www.khronos.org/sycl/) |
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6. [CyCL](https://www.khronos.org/sycl/) | |
6. [SYCL](https://www.khronos.org/sycl/) |
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# Print Formatting |
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Title needs to be updated.
- Good, supported by most common C++ compilers | ||
- Good, support for multiple cores and vector instructions | ||
- Good, requires simple annotations of existing for-loops | ||
- Bad, weak support for advanced hardware (GPU code) |
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This is not the case, OpenMP can target GPUs. It is only in the latest spec IIRC but there is support for at least some Nvidia GPUs from what I recall.
moves the code base into a position that will be easier to parallelize | ||
through one of the GPU libraries | ||
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||
### 3) CyCL |
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And throughout the following paragraphs.
Fair comment. Depends how much detail we want to go in to here, but happy to chip in on this bit. |
On second thought, it is more the kind of information I would expect in a design document and not too relevant here. |
Does everyone feel this matches our discussion from the sprint review?