Thursday, October 28, 2010

max throughput vs max concurrency

I now feel this is a a bit too academic. In practice, I feel concurrency is a technique to achieve throughput.

“max concurrency” is a system feature and probably means “full exploitation of processor and threading capacity”. I know a single SUN processor can have 4 cores and 32 concurrent kernel threads. In such a system, it’s also possible to create user-level threads so total concurrent threads can far exceed 32. I would think thousands are possible.

“max throughput” is a tangible benefit. I think it’s measured by the max number of completed requests per second. The highest throughput is usually achieved in latency-insensitive batch systems rather than synchronous or asynchronous request/response. The fastest way to transfer billions of terabytes of data is to load flash drives on trucks and ship to the receiving site – batch mode.

Max throughput requires finding out bottlenecks. Throughput of a given system is the throughput of the “narrowest” or “slowest” link on the critical path. Adding concurrency to the bottleneck spots (not other spots) improves throughput. For a realistic system, people would buy the max amount of memory they can afford to avoid hitting disk, put in a lot of processors, and somehow multiplex I/O. In low-latency systems, network I/O is often the biggest latency contributor. People use java NIO and exchange collocation, among other things.

Other concurrency techniques include partitioned table, parallel query, disk array, grid and cloud computing.

By “narrowest” I mean the high-way. The more lanes, the better the throughput. A 32-thread processor has 32 lanes. Each thread has a capacity limited by clock speed and software synchronization – that’s what I mean by “slowest”.

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