Disk optimization for multithreaded app.

Mine is a disk based backup/restore product. It is multithreaded,
which means many backups and restores are happening simultaneously.
The product has basically three types of interactions with the disk.



1. Read. This is synchronous. Most reads happen on mounted
shadow copies (using VSS).

2. Write. FILE_FLAG_WRITE_THROUGH is used since data integrity
is critical to the product.

3. Compute checksums on the files.



Each of the above operations are done in their own dedicated threads
and currently any number of threads can be run at any point in time
doing any of the operations in parallel. Each operation targets
exactly one LUN. The size of the data varies from few KBs to Giga
bytes. Also, we may suggest clients to optimize their disk
architecture (use RAID, faster disks, etc.) but the clients may choose
to ignore suggestions.



My questions are,

1. We have noticed that when we run a Read thread and a compute
checksum thread in parallel against the same disk/spindle the disk
throughput degrades considerably and serializing the two threads gives
us much higher throughput overall. Is this behavior expected?

2. If the behavior in 1. is expected then how should we
serialize/parallelize the three kinds of threads to achieve optimal
performance.

3. Are there Windows APIs to determine the spindles we are
working against and throttle our threads accordingly to achieve
optimal performance?

4. Any pointers to case studies, experiments or white papers/
research papers by folks who have done this before?