I started developing HALO portfolio-optimization software just shy of 1.5 years ago. I owned a Linux workstation with a simple RAID-1 file system running Debian Linux, and I was on a 8-week sabbatical from work. I started development using Ruby 1.8.7. Later I switched to Ruby 1.9.1, then 1.9.3. I have chosen, for now, to remain “frozen” on the 1.9.3 Ruby implementation.
I chose Ruby as my primary prototyping language because it allows rapid development, intuitive and highly-readable code, and easy of debugging. Moreover, the Ruby HALO code is highly portable: The code developed Linux ran identically on Window with little to no modification. After the initial development push that produced 3-D optimization graphs, I began developing on Windows under Cygwin. I did this for three reasons. 1) I wanted to run and test on Windows, 2) I had a Windows laptop and wanted to be able to develop anywhere: at the park, at the coffee shop, on an airplane, etc. 3) I wanted to bring and demo my software to potential investors and potential clients. I periodically sync the code between my Windows laptop and my Linux desktop.
Eventually, I began to wonder how much run time performance I was giving up by using Ruby instead of C/C++. I profiled the Ruby code and began re-implemented the most compute-time-intensive parts of the code in C/C++. Finding C++ a bit lacking by itself, I began using C++11 with Boost. I am currently using Boost 1.53.0.
I was expecting perhaps a 10X speed up, but was happily surprised that I saw speed ups of between 20X and 50X when converting from Ruby to C++. The C/C++ implementation is not a line-by-line parroting of the Ruby code, but the algorithms remained the same. Coding in C/C++ caused me to focus more on memory allocation and, yes, garbage collection, so I attribute part of the massive speed up to that.
(I also tried JRuby — compiling the Ruby code to Java bytecode and running on the JVM. I did see a speedup, but only about 15%.)
To date I have converted less than half of the Ruby to C++. Currently the complete HAL0 Suite is 70% Ruby, 26% C++, and 4% other (Perl, Shell, etc). By converting the most critical algorithms to C++, overall run time has improved approximately 3.5X. Less than 10% of the end-to-end run time is consumed by the C++ portion. That leads me to believe that an additional 10X performance increase is likely by the time I convert to a 100% C++ implementation. [All of my run-time benchmark data are based on runs on an Intel(R) Core(TM) i5-2467M CPU @ 1.60GHz.]
My current C++ compiler is gcc 4.5.3. All the C++ benchmarks above were performed with no compiler optimization (-O0). Simply switching to “-O2″ optimization resulted in a 15.6% performance boost. I plan on experimenting with other flags starting with some suggestions from this GCC Intel x86 performance webpage. I will admit I have a bias toward Intel hardware. That being said, it likely be a long time before I choose to plunk down $699 x 2 of Sigma1 Financial’s capital to buy even the basic Intel C++ compilers for Windows and Linux.
I ordered an Intel Core i7-4770K (desktop) system for Sigma1 Financial within a day of the chip’s official release. It is scheduled to arrive next week. Naturally, I am excited to see how much performance gain results from jumping two CPU generations and over 2X in core frequency.