The past half year of SAT and SMT

It’s been a while I have blogged. Lots of things happened on the way, I met people, changed countries, jobs, etc. In the meanwhile, I have been trying to bite the bullet of what has become of CryptoMiniSat: last year, it didn’t perform too well in the SAT competition. In the past half year I have tried to fix the underlying issues. Let me try to explain what and how exactly.

Validation and cleanup

First, in the past years I ‘innovated’ a lot in directions that were simply not validated. For example, I have systems to cleanly exit the solver after N seconds have passed, but the checks were done by calling a Linux kernel function, which is actually not so cheap. It turned out that calling it took 3-5% of the time, and it was essentially doing nothing. Similar code was all over the place. I was (and still am, in certain builds) collecting massive amounts of solving data. It turns out, collecting them means not having enough registers left to do the real thing so the ASM code was horrific and so was performance. The list could go on. In the end, I had to weed out the majority of the stuff that was added as an experiment without proper validation.

Other solvers

Second, I started looking at other solvers. In particular, the swdia5by solver by Chanseok Oh. It’s a very-very weird solver and it performed exceedingly well. I’m sure it’s on the mind of many solver implementers, and for a good reason. As a personal note, I like the webpage of the author a lot. I think what s/he forgets is that MiniSat is not so well-used because it’s so well-performing. Glucose is better. It’s used because it’s relatively good and extremely well-written. However, the patches on the author’s website are anything but well-written.

The cloud

Finally, I worked a lot on making the system work on AWS, the cloud computing framework by Amazon. Since I don’t have access to clusters like my competitors do, I need to resort to AWS. It’s not _that_ expensive, a full SATComp’14 run sets me back about $5-6. I used spot instances and a somewhat simple, 1000-line python framework for farming out computation to client nodes.<

Conclusions

All in all, I’m happy to say, CryptoMiniSat is no longer as bad as it was last year. There are still some problems around and a lot of fine-tuning needed, but things are looking brighter. I have been thinking lately of trying to release some of the tools I developed for CryptoMiniSat for general use. For example, I have a pretty elaborate fuzz framework that could fuzz any solver using the new SAT library header system. Also, the AWS system could be of use to people. I’ll see.