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copied!<p>I'm not familiar with the specifics of your problem, but it sounds a lot like <a href="http://en.wikipedia.org/wiki/Hazard_%28computer_architecture%29#Eliminating_hazards" rel="nofollow noreferrer">data hazards</a> in pipeline CPUs.</p> <p>In your case you want to maximize the utilization of your functional units (streams) without introducing data hazards. Maybe you can write a simple scheduler that looks ahead into the next n instructions and schedules them on to streams?</p> <pre><code>/** * Keeps track of which stream is scheduled to process each account. * If an account is not currently scheduled to be processed, it doesn't appear in the keySet of this map. */ Map<Account, Stream> accountsInFlight; // use a synchronized implementation void schedule(Instruction instruction) { // If the input account is in flight somewhere, use that stream if (accountsInFlight.containsKey(instruction.getInAccount())) { scheduleToStream(instruction, accountsInFlight.get(instruction.getInAccount())); // If the output account is in flight somewhere, use that stream } else if (accountsInFlight.containsKey(instruction.getOutAccount())) { scheduleToStream(instruction, accountsInFlight.get(instruction.getOutAccount())); // If neither are in flight, this is a good candidate for parallel execution, // put it in a different stream } else { Stream stream = // pick a stream (maybe the one with the shortest queue?) scheduleToStream(instruction, stream); } } private void scheduleToStream(Instruction instruction, Stream stream) { stream.addToQueue(instruction); // Update accountsInFlight accountsInFlight.put(instruction.getInAccount(), stream); accountsInFlight.put(instruction.getOutAccount(), stream); } // Remove accounts from the map when the instruction completes </code></pre> <p>Note that this is all fake code: it's not optimized nor does it cover all cases correctly, but maybe it'll give you some ideas to get started.</p>

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