Question

Scenario : I have a sample application and I have 3 different system configuration –

- 2 core processor, 2 GB RAM, 60 GB HHD,
- 4 core processor, 4 GB RAM, 80 GB HHD,
- 8 core processor, 8 GB RAM, 120 GB HHD

In order to effectively exploit the H/W capabilities for my application, I wish to configure the no. of threads at the application level. However, I wish to do this only after a thorough understanding of system capabilities.

Could there be some way(system/modus/tool) to determine the system prowess with reference to the max and min no. of threads it could service optimally & without any loss in efficiency and performance. By this, I could configure only those values for my application that will do full justice and achieve best performance for the respective hardware configuration.

Edited1 :
Could any one please advise any read-up on how to set a baseline for a particular h/w config.

Edited2 :
To make it more direct – Wish to learn/know about any resource/write-up that I can read to gain some understanding on CPU management of Threads at a general/holistic level.

Answer 1

The optimal number of threads to use depends on several factors, but mostly the number of available processors and how cpu-intensive your tasks are. Java Concurrency in Practice proposes the following formal formula to estimate the optimal number of threads:

N_threads = N_cpu * U_cpu * (1 + W / C)

Where:

• N_threads is the optimal number of threads
• N_cpu is the number of prcessors, which you can obtain from Runtime.getRuntime().availableProcessors();
• U_cpu is the target CPU utilization (1 if you want to use the full available resources)
• W / C is the ratio of wait time to compute time (0 for CPU-bound task, maybe 10 or 100 for slow I/O tasks)

So for example, in a CPU-bound scenario, you would have as many threads as CPU (some advocate to use that number + 1 but I have never seen that it made a significant difference).

For a slow I/O process, for example a web crawler, W/C could be 10 if downloading a page is 10 times slower than processing it, in which case using 100 threads would be useful.

Note however that there is an upper bound in practice (using 10,000 threads will generally not speed things up, and you would probably get an OutOfMemoryError before you can start them all anyway with normal memory settings).

This is probably the best estimate you can get if you don’t know anything about the environment in which your application runs. Profiling your application in production might enable you to fine tune the settings.

Although not strictly related, you might also be interested in Amdahl’s law, which aims at measuring the maximum speed-up you can expect from parallelising a program.