of storage, compute, and network resources. We describe a scheduling framework that addresses these problems. Within this framework, data movement operations may be either tightly bound to job scheduling decisions or performed by a decoupled, asynchronous process on the basis of observed data access patterns

approach that combines low-overhead information gathering of database access and storage usage patterns with efficient analysis to generate accurate and timely hints for the administrator regarding data movement operations. STORM’s primary objective is minimizing the volume of data movement required (to

of storage, compute, and network resources. We describe a scheduling framework that addresses these problems. Within this framework, data movement operations may be either tightly bound to job scheduling decisions or, alternatively, performed by a decoupled, asynchronous process on the basis of observed data

distributed module that can be installed on top of a typical NoSQL data-store and provide an efficient and highly configurable load balancing mechanism. Balancing is performed by simple message exchanges and typical data movement operations supported by most modern NoSQL data-stores. We present the system’s

gathers compile time reuse information coupled with array dependence information, rewritesloops to use a truly minimal amount of local memory, and generates the necessary explicit data movement operations for the simple, software exposed hierarchical memory system ofthe M.I.T. RAW machine. Thesis

collaborating institutions, data handling and scheduling problems have reached a new scale. In this paper, we present a new data scheduling model with advance resource provisioning, in which data movement operations are defined with earliest start and latest completion times. We analyze timedependent resource

and receive one message during a bus cycle. Pipelined bus interconnection requires us to rethink how we write parallel algorithms. Fully exploring the properties of concurrent message transmissions requires careful mapping of data, an efficient addressing mechanism, and a set of efficient basic data movement

dependence information, rewrites loops to use a truly minimal amount of local memory, and generates the necessary explicit data movement operations for the simple, software exposed hierarchical memory system of the M.I.T. RAW machine.

-2, as a prototype for real fine grained machines with a hypercubic architecture, fits to the standard hypercube model. We present the implementation of some basic data movement operations in cmis, an assembler language for the cm-2. As a case-study for computational geometry problems we present

…sP; tQ =… gcd…s; t Q in the destination distribution. From the source/destination processor/data sets of array elements in the first generalized basic-cycle, we can construct packing/unpacking pattern tables to minimize the data-movement operations. Since each generalized basic-cycle has the same