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can reading from disk from difference threads optimize program?

I am wondering is there a way to optimize reading from disk in java. I mean for example I want to print the contains of all text files in some directory, but after uppercase them. I can create another thread do uppercase them, but can I optimize reading by adding another(thread(s)) to read files too? I mean 2,3 or more threads to read difference files from disk. Is there some optimization for doing this or not? I hope that I explain the problem clearly.

I want to print the contains of all text files
This is most likely your bottleneck. If not, you should focus on what you bottleneck is as optimising anything else is likely to complicate your code for no benefit.
I can create another thread do uppercase them,
You can, though passing the work to another thread could be more expensive than making it uppercase depending on how your do this.
can I optimize reading by adding another(thread(s)) to read files too?
Possibly. How many disks do you have. If you have one disk, it can usually only do one thing at a time.
I mean 2,3 or more threads to read difference files from disk.
Most desktop drives can only do one operation at a time.
Is there some optimization for doing this or not?
Yes, but as I said, until you know what your bottleneck is, it's hard to jump to a solution.

I can create another thread do uppercase them
That's actually going in the right direction, but simply making all letters uppercase doesn't take enough time to really matter unless you're processing really large chunks of the file.
Because the standard single-threaded model of read-then-process means you're either reading data or processing it, when you could be doing both at the same time.
For example, you could be creating a series of highly compressed (say, JPEG2000 because it's so CPU intensive) images from a large video stream file. You could have one thread reading frames from the stream, placing them into a queue to process, and then have N threads each processing a frame into an image.
You'd tune the number of threads reading data and the number of threads processing data to keep both your disks and CPUs maximally busy without excess contention.
There are some cases where you can use multiple threads to read from a single file to get better performance. But you need a system designed from the ground up to do that. You need lots of disks (less so if they're SSDs), a pretty substantial IO infrastructure along with a system that has a lot of IO bandwidth, and then you need a file system that can handle multiple simultaneous access to a single file. Then the code you have to write to get better performance from reading using more than one thread has to match things like the physical layout of your files on disk.
That works best if you're doing lots of random reads from a file spread over multiple devices. Like a large, high-powered database server.
For example, lets say I have a huge data file spread over four or five disks (or even RAID arrays), with the file spread out over the disks in 64KB chunks. A handful of threads doing 64KB reads would be ideal to read or write such a file in a random-access mode. Let's say everything is really fast and you can read or write 1 GB/sec from such a file.
But if you turn around and just try to copy that data in a stream, you can still use multiple threads to get maximum performance - say 1 GB/sec - but if you just used a single thread to do read() calls in 1 MB chunks you'd probably get 950 MB/sec - or 95% or maximum multithreaded read performance.
I've actually benchmarked such systems and most of the time, multithreaded IO isn't worth the trouble unless you've invested a lot of money in your hardware and software (opensource file systems tend not to do this very well - you need to get into the realm of IBM's GPFS and Oracle's (nee LSC's then Sun's) QFS) and you know exactly what you're doing when you set it up.

Maintaing a map of buffered stream and closing in the end

My applications does continuous disk i/o through 10 threads. The cpu profile is coming very high around 100%, i was planning to make it to 1 separate writer thread.
Also I was thinking if i can maintain a Cache of Buffered Writers and so do not have to continuously open the streams. Does anyone see a problem in this
But I am unsure of where to put the close the writer. Secondly if the writer are not closed will there be a problem.
Thanks

If you are writing short strings to the writers very often, opening a new writer might indeed be a waste of time. One issue to be aware of is that if you keep the streams open, other threads trying to write to the same file may fail. From the FileOutputStream documentation:
Some platforms, in particular, allow a file to be opened for writing by only one FileOutputStream (or other file-writing object) at a time.
Also, make sure you put the closing statement in a finally clause.
PS Björn is right, IO is unlikely to show up as CPU usage. Run a profile to work out what the app is actually doing

IO itself is unlikely to cause CPU load.
The character encoding conversions involved when converting strings from Java's internal representation to UTF8, ISO-Latin-1 or whatever the encoding it is that you are using, however does cause CPU load.
10000 lines per minute isn't that much, though. Only about 7000 characters per second (for 40 character lines). Or was that 10000 lines for each thread?

FileInput/OutputStream versus FileChannels -- which gives better performance

I am writing a program that has to copy a sizeable, but not huge amount of data from folder to folder (in the range of several dozen photos at once). Originally I was using java.io.FileOutputStream to simply read to buffer and write out, but then I heard about potential performance increases using java.nio.FileChannel.
I don't have the resources to run a serious, controlled test with the data I have, but there seems to be no consensus on what the advantages of each are (other than FileChannel being thread safe). Some users report FileChannel being great for smaller files, others report huge speed increases with larger files.
I am wondering if anyone knows exactly what the intent of creating FileChannel was in the first place: was it designed for better performance? In what cases? And is there a definitive performance increase for general kinds of data, or are the differences I should expect to see trivial because I am not working with data that is specialized enough?
EDIT: Assume my data does not need to be thread safe.

FileChannel.transferFrom/To should be faster than IO stream for file copying.
Or you can simply use Java 7's java.nio.file.Files.copy(source, target). That should be as fast as it can get.
However, in the end, performance won't be noticeably different - hard disk speed is the bottleneck.
FileChannel is not non-blocking, and it is not selectable. Not sure if they are going to add these features in future. Java 7 has AsynchronousFileChannel though.

Input and Output Streams assume a stream styled access to the file or resource. There are a few extra items which help (array reads) but the basic idea is that of a stream where you read in one or more characters at a time (possibly blocking until you have more characters available).
Channels are the means to copy information into Buffers. This provides a lower level of access to input and output routines. With thoughtful buffer sizing, the speed-ups can be impressive. Structuring your code around buffers can reduce the time spent in a read loop (also increasing performance). Finally, while it is possible to do pre-checking of input stream state in an attempt to avoid blocking, Channels and Buffers allow operations to perform in a non-blocking manner (even in the worst conditions).

Have you take a look at commons-io?
FileUtils.copyFileToDirectory(srcFile, destDir);

What about buffering FileInputStream?

I have a piece of code that reads hell of a lot (hundreds of thousand) of relatively small files (couple of KB) from the local file system in a loop. For each file there is a java.io.FileInputStream created to read the content. The process its very slow and take ages.
Do you think that wrapping the FIS into java.io.BufferedInputStream would make a significant difference?

If you aren't already using a byte[] buffer of a decent size in the read/write loop (the latest implementation of BufferedInputStream uses 8KB), then it will certainly make difference. Give it a try yourself. Don't forget to make any OutputStream a BufferedOutputStream as well.
But if you already have buffered it using a byte[] and/or it after all makes only little difference, then you've hit the harddisk and I/O controller speed as the bottleneck.

I very much doubt whether that will make any difference.
Your fundamental problem is the hundreds of throusands of tiny files. Reading those is going to make the disk thrash and take forever, no matter how you do it, you'll spend 99,9% of the time waiting on mechanical movement inside the harddisk.
There are two ways to fix this:
Save your data on an SSD - they have much lower (as in five orders of magnitude less) latency.
Rearrange your data into few large files and read those sequentially

That depends on how you're reading the data. If you're reading from the FileInputStream in a very inefficient way (for example, calling read() byte-by-byte), then using a BufferedInputStream could improve things dramatically. But if you're already using a reasonable-sized buffer with FileInputStream, switching to a BufferedInputStream won't matter.
Since you're talking a large number of very small files, there's a strong possibility that a lot of the delay is due to directory operations (open, close), not the actual reading of bytes from the files.

Buffer a large file; BufferedInputStream limited to 2gb; Arrays limited to 2^31 bytes

I am sequentially processing a large file and I'd like to keep a large chunk of it in memory, 16gb ram available on a 64 bit system.
A quick and dirty way is to do this, is simply wrap the input stream into a buffered input stream, unfortunately, this only gives me a 2gb buffer. I'd like to have more of it in memory, what alternatives do I have?

How about letting the OS deal with the buffering of the file? Have you checked what the performance impact of not copying the whole file into JVMs memory is?
EDIT: You could then use either RandomAccessFile or the FileChannel to efficiently read the necessary parts of the file into the JVMs memory.

Have you considered the MappedByteBuffer in java.nio? It's over my head but maybe it is what you are looking for.

I doubt that buffering more than 2gb at a time is going to be a huge win anyway. Depending on the amount of processing you're doing, you might be able to read in nearly as fast as you process. To speed it up, you might try using a two-threaded producer-consumer model (one thread reads the file and hands the data off to the other thread for processing).

The OS is going to cache as much of the file as it can, so trying to outsmart the cache manager probably isn't going to get you very much.
From a performance perspective, you will be much better served by keeping the bytes outside the JVM (transferring huge chunks of data between the OS and JVM is relatively slow). You can achieve this goal by using a MappedByteBuffer backed by a direct memory block.
Here's a pertinent how-to type of article: article

I think there are 64 bit JVMs that will support nonstandard limits.
You might try buffering chunks.