Some of the research findings from these areas of work can be found on our publications page. It provides a high-level API that abstracts concurrent task management details Is a simple and effective way of adding task parallelism to SPMD programs. In order to help find and correct data races,ĭeadlocks and other programming errors, we are working on Active Testing: UPC programs can have classes of bugs not possible inĪ programming model such as MPI.Space model is especially appropriate when the communication is asynchronous. This effort will also allow us to determine the potential for optimizationsĪpplications with fine-grained data sharing benefit from the lightweightĬommunication that underlies UPC implementations, and the shared address Targeting problems with irregular computation and communication patterns. To demonstrate the features of the UPC language and compilers, especially Application benchmarks: The group is working on benchmarks and applications.Of shared pointer manipulation when accesses are known to be local. We are also examining optimizations based on avoiding the overhead Or a shared array with 'indefinite' blocksize (i.e., existing entirely on one Programmer uses either the default, cyclic block layout for distributed arrays, We are implementing optimizations for the common special cases in UPC where a "relaxed " consistency semantics, which can be exploited by the compiler to hideĬommunication latency by overlapping communications with computation and/or UPC allows programmers to specify memory accesses with Network communication, aggregate communication into more efficient bulk Is working on developing communication optimizations to mask the latency of Compilation techniques for explicitly parallel languages: The group.Have adopted GASNet for their PGAS networking requirements. Which currently runs over a wide variety of high-performance networks (as well Low-level, portable networking library), you should look at our GASNet library, Implementing your own global address space language (or otherwise need a UPC-specific parts our runtime layer from the networking logic. In an effort to make our code useful to other projects, we have separated the Our group has thus developed a lightweight communicationĪnd run-time layer for global address space programming languages. Most efficient hardware mechanisms available. It is therefore important that the overhead of accessing the underlyingĬommunication hardware is minimized and the implementation exploits the In order to be able to obtain good performance from an implementation, the granularity ofĪn access is often the size of the primitive C types - int, float, double). Remote data is accessed with a low granularity (i.e. Memory abstraction that it offers, UPC encourages a programming style where References to remote shared variables usually translate into calls to aĬommunication library. Lightweight Runtime and Networking Layers: On distributed memory hardware,.Goals are portability and high-performance. Implementation of UPC for large-scale multiprocessors, PC clusters, andĬlusters of shared memory multiprocessors. The goal of the Berkeley UPC team is to develop a portable, high performance The Berkeley UPC compiler suite is currently maintained primarily by theĪt Lawrence Berkeley National Laboratory. The programmability advantages of the shared memory programming paradigmĪnd the control over data layout and performance of the message passing UPC is not a superset of these three languages,īut rather an attempt to distill the best characteristics of each. Languages that proposed parallel extensions to ISO C 99: ACĬ Preprocessor (PCP). The UPC language evolved from experiences with three other earlier Synchronization primitives and a memory consistency.In order to express parallelism, UPC extends ISO C 99 with the following The amount of parallelism is fixed at program startup time, typically withĪ single thread of execution per processor. Uses a Single Program Multiple Data (SPMD) model of computation in which Space, where variables may be directly read and written by any processor,īut each variable is physically associated with a single processor. Programmer is presented with a single shared, partitioned address The C programming language designed for high performance computing on large-scaleĪ uniform programming model for both shared and distributed memory hardware.
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