DeanoC thoughts and musings

The need for speed Coming from a real-time world (games and graphics), current machine learning training is a shock. Even small simple training tasks take a  long  time, which gives me plenty of time to think about the performance of my graphs. Currently most of the open source deep learning stacks consist of a C++ and Cuda back-end driven by a Python/R/Lua front end. The Cuda code tends to be fairly generic, which makes sense from an HPC and experimental point of view.  Its important to note HPC stuff is very optimised but tends to really on standard interfaces with relatively custom generic back-ends. For example BLAS is a old FORTRAN standard for linear algebra, it  has numerous back-ends included optimised x64, Cuda, OpenCL etc.  However it only accelerates the tensor multiplies in a few data formats, other more data specific optimisation like overlapping conversions isn't in its remit. Its quite a different optimisation strategy from the rea...

Flu and strange Ideas I have a cold/flu thing at the moment and feel rotten, due to interaction with my general health when I get even a mild cold or flu I get pain everywhere and due to the levels of pain killer I take normally, I just have to grin and bare it. The way I tend to cope is to keep my mind occupied to try and not think about it. Strangely this is often a creative time in terms of random thoughts, I guess the body pushes more natural drugs into me to try and counteract the pain leading to me being a bit 'drugged'. Thinking about teaching (not training) AIs Last night I was deep in thought about Deep AIs, as you may have noticed from my recent blog posts is something I'm really enjoying and TBH can see myself working in the field. Before the fame of the recent AlphaGo wins, Deepmind were tackling other simpler games from the Atari 2600 machine. The paper "Human-level control through deep reinforcement learning" successfully learnt to play a number...

Its a lie because it implies there is a 'premature' aspect to writing code, that you shouldn't worry about performance or power at some phase of the research/project. Its simple not true, there are time when its not the greatest priority but thinking about how it affects these areas is never wasted. At some fundamental level, software is something that takes power (electricity) into math. Anytime you don't do it optimally you waste power.  The only time that doesn't matter is when you have a small problem and lots of power, in practise few interesting problems are lucky to get away with that. If you work in machine learning or big data, the likely limit to what you can do is related to how many processors (wether they are CPU, GPU or FPGA) you can throw at the problem. Assuming you can't scale infinitely, then the results you can get out of a finite set of HW will largely be determined by how performant your code is. When you've designed your latest ...

I've been studying AI tech a fair bit recently for a variety of reasons. There are lots of areas I want to explore using AI as solvers/approximations but as someone whom is generally employed to do graphics stuff, there always an interest in the application of AI technology to rendering. Currently except for a few papers on copying artistic styles to photos, its not yet a major discipline. The real big thing to take aware from AI like deep neural nets, is that they are approximate function solvers that are taught via showing them the data rather than be explicitly programmed. Once trained they evaluate the inputs, through there learnt 'function' and give you a result. With enough nodes and layers in the network and a lot of training, they can give a solution to any equation you have existing data for. In rendering, the classic Kajiya equation is the solution real and offline renderers attempt to solve. The reason why rendering takes some much compute power, is t...

I was lucky enough to grow up in the era when home computer and consoles were new, and movies using CG was something worth talking about if anybody actually used managed to actually used it (i'm looking at you Max Headroom and Tron, both designed to look like CG but mostly used old fashioned effects as computers weren't fast enough). One of my favourite movies didn't (AFAIK) use CG but now would use it a lot, Who Framed Roger Rabbit . Roger Rabbit is a clever comedy/who dun it about a murder with the main suspect being the eponymous Roger Rabbit. The twist is that Roger Rabbit is a rabbit, a cartoon rabbit. The world is set up so that Hollywood has a section called Toon Town, where cartoons actually exist. Bugs Bunny, Micky Mouse actually exist and act in TV shows and movies just like other actors. The star (apart from Roger) is Eddie Valiant played by Bob Hoskins who is a classic 20/30s grizzled private eye who hates Toons after one kills his partner. The part ...