Computer Engineering Commons^™

Is Parallel Programming Hard, And If So, Why?, Paul E. Mckenney, Maged M. Michael, Manish Gupta, Philip William Howard, Josh Triplett, Jonathan Walpole

Computer Science Faculty Publications and Presentations

Of the 200+ parallel-programming languages and environments created in the 1990s, almost all are now defunct. Given that parallel systems are now well within the budget of the typical hobbyist or graduate student, it is not unreasonable to expect a new cohort in excess of several thousand parallel languages and environments to appear in the 2010s. If this expected new cohort is to have more practical impact than did its 1990s counterpart, a robust and widely applicable framework will be required that encompasses exactly what, if anything, is hard about parallel programming. This paper revisits the fundamental precepts of concurrent …

Dynamic Task Prediction For An Spmt Architecture Based On Control Independence, Komal Jothi

Dissertations and Theses

Exploiting better performance from computer programs translates to finding more instructions to execute in parallel. Since most general purpose programs are written in an imperatively sequential manner, closely lying instructions are always data dependent, making the designer look far ahead into the program for parallelism. This necessitates wider superscalar processors with larger instruction windows. But superscalars suffer from three key limitations, their inability to scale, sequential fetch bottleneck and high branch misprediction penalty. Recent studies indicate that current superscalars have reached the end of the road and designers will have to look for newer ideas to build computer processors.

Speculative …