Trading system in c++
C++ Software Engineers – Top High Frequency Trading Team | Campbell North
He thinks array out of bounds errors are difficult to debug. The chances of him understanding how important memory access patterns are for performance is nil. Also, if the app perform any DB access to query data to help your decision, it may be take another bunch of ms! High-frequency trading and high-performance computing uses networks like Solarflare or Mellanox, which have about 1 us of overhead. And same-node interprocess communication uses shared memory, which is half that.
Whatever the network latency the app can not start processing the data until it has arrived and so the app latency will be an additional overhead on top of any network overhead. So to say, anything that really needs to crunch numbers as fast as possible and requires a lot of memory manipulation, custom memory management systems, etc.
Also, for example, games make a big use of SIMD compiler intrinsics to utilise the CPU cores as much as possible where the GPU is already filled with tons of graphics work at this time. You can grab a chunk of memory and make any change you want in it. My experience using Java for low latency inference services for advertising click prediction has yielded me a ton of frustration managing off heap memory and wrestling with the garbage collector. A managed language will never compete in low latency with an unmanaged language. The fact alone that Java has a garbage collector by default would slow it down.
Post some benchmarks. NET release. Who told you that C is faster than Java? C faster than Java? Stats to back that claim?
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C is absolutely faster than Java. It has more thorough support for value semantics. You are only allocating when necessary. Also, not that this conversation is about this, it is much easier to write and read. Namely, it is easier and faster to develop in C than Java. It is after all more elegant than Java, being essentially a refinement of Java.
The traditional claim that you spend hours debugging is simply not true. Stop spreading lies!
I would say that the title is misleading. All the effort is made to express that Java code is written quicker and with higher maintainability. If you need faster execution time, or faster development, depends on the domain. If I were to write a mathematical number-crunching library, where the latency would be the only reason to choose one library over another, it would probably be a fatal mistake to write it in Java.
Easier to write, maintain and therefore getting people up to speed are valid Business needs. Same goes for transcoded approaches. To be fair there might be Business cases for the middle ground focused in this article but they are never evaluated, explained or put into numbers. This is accurate. Scala is better for general purpose app development. Python is good for scientific programming due to its excellent numpy library and the large ecosystem of statistical libraries built around it.
Java is a not a bad legacy language running on a very good jvm platform. It is not the best of any breed but is often a convenient compromise. Did they use every corner of the library in their unit tests? I agree with you there. WAY worse. This could mean skips for audio, triggering an airbag late, or failing to process an item on an assembly line. It does odd things when you are memory unsafe. The problem with Java is that performance is hard to predict. If I avoid allocations in a loop, the JVM is still allowed to trigger garbage collection in the middle of it.
This makes tracking down slowness hard. Non-deterministic execution time is a failure.
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No-one wants horrific software virtual machines in critical applications. Please study your field a bit more before rambling stuff like this. I also taught. I found backpropagation code in C and in Python for ideas.
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The Python code was undoubtedly faster because it was more efficient. The cryptic C code had a major inefficiency. But HFT! HFT is a market maker and ideally at the end of the day you up with no position at all. Jitter is not. That way all the branches etc are taken as if we really were sending an order, just the hardware drops the result. But here we are talking microseconds and up to milliseconds rather than nanoseconds — many factors above the requirements for HFT. Disclaimer — I am not a HFT developer but work closely on projects with a number of developers who are.
A textbook definition of a hard real-time system. No java application can handle such a requirement. I am also not a HTF developer, but I am quite familiar with real-time systems for various use cases. And this looks like one of them to me.
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This is the most on-target comment so far. The jitter consideration alone tanks java with its VM as a consideration. Java is getting better but it is not afaik a candidate for HFT or other hard real-time apps.
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The only way that could change is by using a hard-realtime jvm. My understanding is that such a jvm has not existed for many years. Thanks, exactly what I was going to reply. Sometimes a screwdriver sometimes a saw. For some cases devs want to decide on the memory layout of objects in memory and not worry about the VM or cache misses etc… Same reason as why webassembly became a thing in browsers.
Also did you notice there are languages like RUST that are quite popular on Stackoverflow these days? JS does not do HFT. They do some form of algo trading. Firms do algo trading in a lot of languages: Python, Java, OCaml etc. This has to be one of the most baffling articles I have read in a while.