Higher global bandwidth requirement for many applications and lower network cost have motivated the use of the Dragonfly network topology for high performance computing systems. In this paper we present the architecture of the Cray Cascade system, a distributed memory system based on the Dragonfly [1] network topology. We describe the structure of the system, its Dragonfly network and the routing algorithms. We describe a set of advanced features supporting both mainstream high performance computing applications and emerging global address space programing models.We present a combination of performance results from prototype systems and simulation data for large systems. We demonstrate the value of the Dragonfly topology and the benefits obtained through extensive use of adaptive routing.

A parallel sorting algorithm for sorting n elements evenly distributed over Zd = p nodes of a d-dimensional hypercube is presented. The average running time of the algorithm is O((n log n)/p + p log2 n). The algorithm maintains a perfect load balance in the nodes by determining the (kn/p)th elements (k = 1,.. . , (p-1)) of the final sorted list in advance. These p-1 keys are used to partition the sorted sublists in each node to redistribute data to the nodes to be merged in parallel. The nodes finish the sort with an equal number of elements (n / p) regardless of the data distribution. A parallel selection algorithm for determining the balanced partition keys in O(p log2 n) time is presented. The speed of the sorting algorithm is further enhanced by the distanced communication capability of the iPSC/2 hypercube computer and a novel conflict-free routing algorithm. Experimental results on a 16-node hypercube computer show that the new sorting algorithm is competitive with the previous algorithms, and faster for skewed data distributions.

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