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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.
This is good of course, however, whenever I see a spreadsheet program used for any serious computation, I cringe. There are far better tools out there if you require real number crunching. Think Python + Panda for instance, or R, or Matlab if you are really into commercial programs, otherwise a nice interactive web page will usually do the trick. For accounting use a real accounting program, there are plenty out there. Spreadsheet programs are the lowest common denominator that allow the sharing of table-like information, but almost universally they are the wrong tool for the job. 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.
Of course this is software that people know, so usually we have to deal with it. As a rule I accept to work with other people's spreadsheets, but I usually refuse to create one ex-nihilo, unless there is a compelling reason to. For instance I teach a course on optimisation, and I do show how the solver in Excel / {Libre,Open}Office works. I have also on occasion shown people how to use a pivot table (never use those if you can help it).
The most severe problem I see with spreadsheet is that they have their use but they are fragile. It is too easy to load an extensive table into them and inadvertently modify just one cell, potentially undoing a lot of work. This is easy to detect if your spreadsheet is small, but if it span multiple tabs and an ungodly number of rows, you will not detect your error. Of course the format of these spreadsheet is obscure, and version control is typically not supported.
Personally the worst I have seen was one spreadsheet used for the accounting of 90+ separate research projects, spanning 30,000 cells. The accountant in charge of it was the person most attentive to detail I have ever seen. She was careful and the only person using it, which made her indispensable. We put in place a year-long plan for her retirement, involving scrapping her spreadsheet, entirely replacing it with a direct interface with SAP via a php-based web page. It was many months in the making, of course this was not a trivial project but we've pulled it off. In the process we discovered a huge number of accounting errors thanks to it, typically invoices that were never billed, to the tunes of nearly one million dollars. It took us several months to correct them.
The morals of this is never, ever use spreadsheets program for non-trivial work.
"A GPU is not 500 times faster than a CPU, more like 2 or 3 times"
Just on FLOPs alone you're dead wrong. The latest and greatest E-series Xeons (V3) have barely enough power to match the 9800GTX+ - about 800 GigaFLOPs. The 980 GTX Ti is roughly 5.6 TeraFLOPs.
Still waiting on Serviscope_minor to wake up to fucking reality and realize that Jessica Price isn't going to fuck him.
here are my answers. Spreadsheets are used in several cases:
1) When you have a small-to-medium-sized dataset (100m data points) and want to do a particular set of calculations or draw a particular set of conclusions from it just once or twice—so that the time invested in writing code in R or something similar is less than the time needed just to bung a few formulas into a spreadsheet and get your results. Once you get into analyses or processes that will be repeated many times, it makes more sense to write code.
2) Similar case, when you need to work with essentially tabular database data, but the operations you're performing (basic filtering, extracting records based on one or two criteria, just handing data from one person to the next) are either so simple or will be repeated so rarely that a MySQL database is overkill and just emailing a file back and forth is easier.
3) When you are working with data as a part of a team, and certain members of the team that are specialists in some areas related to the data, or (for example) members of the team that are doing your data collections, aren't particularly computationally expert. Spreadsheets are hard for laymen, but it's doable—a dozen or two hours of training and people can get a general, flexible grasp of spreadsheets and formulae. It takes a lot longer for someone to become basically proficient with R, MATLAB, MySQL, Python, etc., and you really want those specialists to just be able to do what they do to or with the data, rather than focusing their time and effort on learning computational tools. Spreadsheets are general purpose and have a relatively shallow learning curve relative to lots of other technologies, but they enable fairly sophisticated computation to take place—if inefficiently at times. They're like a lowest-common-denominator of data science.
We use Spreadsheets all the time in what we do, mostly as a transient form. The "heavy hitting" and "production" data takes place largely in MySQL and R, but there are constant temporary/intermediate moments in which data is dumped out as a CSV, touches a bunch of hands that are really not MySQL or R capable, and then is returned in updated form to where in normally lives.
STOP . AMERICA . NOW
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.
really depends on use case. Our spreadsheets (finance, derivatives) can get damn big, but there are 3 reasons they persist: ease of modification, speed of the interface, and easy integration with powerful analytics libraries we use.
Now I have functioned in a python based environment before, and that had some huge benefits (especially when working on tick level data, or data that was just a pain to manage in VBA until I got output down to a reasonably visualizable size) , and I regularly push for trade level data and details to be put off into a SQL database as it is pretty easy to write flexible queries to get what I want out. But visualizing data, interacting with historic data (user forms for display), generally integrating with many other financial libraries (bloomberg and reuters for realtime, internal quant libraries for complex calculations), and having a fast interface out of the box is amazing.
I've been at places that have tried to replace excel as the interaction layer. The problem is, for all its problems, most coders cannot hack together, on their own, a better GUI that is as performant or easily interacted with. Sometimes it isn't the data analysis layer (which if at all possible, we like to farm off somewhere else for perofrmance), but everything else that makes the spreadsheet far superior. And of course, I can modify and adapt someone else's work far faster than anyone using code. On a regular basis I can build up a complete tool in excel 10-20x faster than any coder can write me something outside of it. And most of the time a 95% correct answer in 1 hour is far more useful than a 100% correct answer in 3 days.
Now saying that, once the office ribbon started, that was the beginning of the end. Slowly the interface is getting too clunky to waste my time with when it was the simplest things I required. Now I try to do a lot of my work in a proper coding language and write out files I can parse quickly in vba and display in excel.
When the only tool you have is a spreadsheet, there is no place to sit because...
That's funny because spreadsheets actually came from accounting. The first spreadsheet wasn't created by a geek or a programmer, it was created by an accountant. It's simply the electronic form of something that was already being done on paper.
Spreadsheets not suitable for finance or accounting?
That's where they came from.
A Pirate and a Puritan look the same on a balance sheet.
It's really amazing what you can do in a spreadsheet.
Several years ago I was involved with management of optical wavelength switching gear (DWDM) in conjunction with a large, national telcom. They had some very well designed tools with very nice GUIs to allow things like building an optical path. Things that require managing complex database and doing a lot of checking on availability of resources and validity of the circuit.
It was all written in Excel!
I was amazed at it all. Nothing looked at all like a spreadsheet. and it actually worked and seemed pretty maintainable. I'm sure that they would have been delighted to see this sort of things as the one issue was the time it took to update the screen when certain changes were made (re-calculation).
Kevin Oberman, Network Engineer, Retired