What grid distributed computing frameworks are currently favoured for trading systems

Question

There seems to a quite a few grid computing frameworks out there, but which ones are actually being used to any great extent by the investment banks for purposes of low latency distributing calculation? I'd be interested to hear answers covering both windows,Linux and cross platform. Also, what RPC mechanisms seem to be favoured most?

I've heard that for reason of low latency and speed, the calculations themselves are quite often written in C++/C as calculations running on VMs are several orders of magnitude slower than native code. Does this seem to be a common scenario in practice? e.g distributed .NET grid framework running calculations written in native c++/c?

Answer 1

Some directions (actually used in some corporate investment banks) :

• Home made solutions involving PC
  farms (traders queue their
  computation requests)
• GPU

since computationally intensive fiancial operations (eg. Monte Carlo pricing) are usually heavily parallelizable.

Answer 2

low latency distributing calculation

'Low latency' and 'distributed' are mutually exclusive :)

But saying that, it depends how low you mean by 'low latency'. If you are talking about High Frequency Trading (HFT), then any implementations are going to be using the fastest networking code they can get their hands on - most likely custom TCP/IP stacks (e.g. OpenOnload, native infiniband etc). The network is always going to be the slowest part of your code, so you need to keep the networking to a minimum.

If you are talking 'fast' but not HFT-fast (like pricing exotic options / structured products), then you can pretty much use anything you like. I've worked on systems that used anything from .Net/RPC, JMS (ActiveMQ), TCP/IP sockets, etc. It's more about the flexibility and ease at which you can define and send data, rather than the raw speed of networking.