Removing randomness in parallel computation without a processor penalty

Removing Randomness in Parallel Computation Without a Processor Penalty

We develop some general techniques for converting randomized parallel algorithms into deterministic parallel algorithms without a blowup in the number of processors. One of the requirements for the application of these techniques is that the analysis of the randomized algorithm uses only pairwise independence. Our main new result is a parallel algorithm for coloring the vertices of an undirecte...

Removing Randomness

In recent years, many probabilistic algorithms (i.e., algorithms that can toss coins) that run in polynomial time have been discovered for problems with no known deterministic polynomial time algorithms. Perhaps the most famous example is the problem of testing large (say, 100 digit) numbers for primality. Even for problems which are known to have deterministic polynomial time algorithms, these...

Non-Interactive Multiparty Computation without Correlated Randomness

We study the problem of non-interactive multiparty computation (NI-MPC) where a group of completely asynchronous parties can evaluate a function over their joint inputs by sending a single message to an evaluator who computes the output. Previously, the only general solutions to this problem that resisted collusions between the evaluator and a set of parties were based on multi-input functional...

Serializing Parallel Programs by Removing Redundant Computation

Programs often exhibit more parallelism than is actually available in the target architecture. This thesis introduces and evaluates three methods|loop unrolling, loop common expression elimination, and loop di erencing|for automatically transforming a parallel algorithm into a less parallel one that takes advantage of only the parallelism available at run time. The resulting program performs le...

Increasing Processor Utilization During Parallel Computation Rundown