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AMD Forces a LibreOffice Speed Boost With GPU Acceleration
New submitter samtuke writes: AMD processors get rated and reviewed based on performance. It is in our self-interest to make things work really, really fast on AMD hardware. AMD engineers contribute to LibreOffice, for good reason. Think about what happens behind a spreadsheet calculation. There can be a huge amount of math. Writing software to take advantage of a Graphics Processing Unit (GPU) for general purpose computing is non-trivial. We know how to do it. AMD engineers wrote OpenCL kernels, and contributed them to the open source code base. Turning on the OpenCL option to enable GPU Compute resulted in a 500X+ speedup, about ¼ second vs. 2minutes, 21 seconds. Those measurements specifically come from the ground-water use sample from this set of Libre Office spreadsheets.
It can be. Don't generalize to use cases you don't know, especially when people with no real programming skills are concerned. I honestly don't know any other software that is both as flexible and accessible as spreadsheets when it comes to doing computations on heaps of (mostly irregular) data.
People use the tools they are familiar with. There are plenty of business types who are goddamn magic wizards with a spreadsheet who completely freeze up at the thought of putting a database together. I've seen spreadsheets clicking over into the 3-400mb range that have been used for years in organizations and you know it could be managed much more efficiently, yet people resist because it's easier for them to make quick modifications than passing along requests to a database admin.
I wonder if a spreadsheet is really the right tool for computations that take several dozens of seconds on modern hardware, even without GPU acceleration. I am inclined to think it is not.
It depends on the nature of the data and the calculation itself. If it is a relatively small data set and does not require relational tables, but a very complicated set of equations, then a spreadsheet might be a reasonable choice vs a database.
AMD engineers have contributed OpenCL code which is an open standard that can run on many different accelerators (some not even GPUs). this is distinctly different from CUDA which only works with Nvidia stuff.
Anons need not reply. Questions end with a question mark.
...Just in the last week, I have seen spreadsheets used for a program logic workflow, a timetable, a university course schedule, to compute an FFT, to exchange student marks, to discuss a budget (with lots of deletions and remarks), and even for a presentation. In each and every case a more suitable, open-source, freely available, multi-platform application exists.
You've just stated the reason people use spreadsheets right there. One multi-purpose program vs umpteen specialist programs, each with their own UI quirks that have to be learned to make the most use of the programs. Why bother when a good old spreadsheet will work.
Depends on what you mean by "faster." If you mean clock frequency, then perhaps. Also perhaps if you mean an individual core of a CPU vs a core of a GPU.
In this sense, it's the time to perform massively parallel instructions. GPUs are generally hundreds of times faster than CPUs for such calculations. Part of this is because a CPU can have a few cores, but a GPU generally has thousands of floating point units. The other part is that CPUs are general purpose central processors while GPUs are very specialized to optimize them for specific kinds of tasks.
Think of it like a CPU is 4 guys with Swiss Army Knives while a GPU is a team of 1,600 guys each with a battery powered, professional screwdriver. Guess which one's faster at screwing 1,600 wood screws into 400 posts for a building. Now guess which is faster at cutting a traced outline on a single piece of paper.
http://www.nvidia.com/object/w...
My opinion of Apple and Apple products has changed. Not that I'd ever buy an Apple product, but I went with a non-technical friend to an Apple store; she wanted me to go along when she bought a new Macbook. I was amazed at the high level of service and the extent of the support structure. She paid twice as much total for her Macbook as I paid for my Asus Zenbook (she bought the training and extended support which added $400 to the total), but she has a level of comfort that is rather high for a non-technical user.
I was pretty impressed, and I can see why people might want to buy the Apple brand. They don't care about the closed design and complete control by Apple. They want to have a place to go to get help and support, of a type and level that they can understand and feel good about. This particular Apple store was packed with people and always is. There's a reason, and I learned what it is that day.
While the intended workflow for data crunching on the desktop is typically served by R/Python/Julia among others, there are times you have to do some processing for a huge amount of data for a spreadsheet you have open in front of you. This is where AMD/LibreOffice will shine and this is a good motive to buy AMD and LibreOffice.
You say you "worked" in HPC. Are you sure your knowledge is still even remotely current? Are you sure your focus on CPU optimisation didn't leave you blind to what everyone else was doing?
In my experience, a good multi-core CPU is good for more like 125 GFLOP/s, and that varies highly from program to program thanks to the highly variable quality of code & compilers. You may be able to eke out better performance than that with skilful optimisation, but the vast majority of commercially available CPU-only software will never be that well optimised, even if it's brand new or rewritten from scratch.
A good GPU can sustain upwards of 5 TFLOP/s at single-precision with very little effort from the developer, and for the vast majority of applications, single precision is more than sufficient. It's not hard at all to fully utilise all that speed. I've ported carefully-optimised, thoroughly-parallelised CFD code from C++ to OpenCL and seen 50x speed gains on the first successful test run. After a little further optimisation it's usually around 100x, and that's not even with a particularly high-end GPU. This sort of thing no longer surprises me. I don't even consider an OpenCL port to be working properly until it's 100x faster than the CPU version.
So the reason you're seeing people making "outlandish" claims of 200x speed-ups thanks to GPUs must be that 200x speed-ups are not unusual, and you just haven't been paying attention. This seems far more likely than everyone else being clueless but still seeing massive speed-ups while you're the one in the know and seeing nothing special at all.