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Berkeley UPC - Unified Parallel C
(A joint project of LBNL and UC Berkeley)
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NEW -- Berkeley UPC version 2.6.0 released!
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The UPC Language
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Unified Parallel C (UPC) is an
extension of
the C programming language designed for high performance computing on large-scale
parallel machines.The language provides
a uniform programming model for both shared and distributed memory hardware. The
programmer is presented with a single shared, partitioned address
space, where variables may be directly read and written by any processor,
but each variable is physically associated with a single processor. UPC
uses a Single Program Multiple Data (SPMD) model of computation in which
the amount of parallelism is fixed at program startup time, typically with
a single thread of execution per processor.
In order to express parallelism, UPC extends ISO C 99 with the following
constructs:
The UPC language evolved from experiences with three other earlier
languages that proposed parallel extensions to ISO C 99: AC
, Split-C, and Parallel
C Preprocessor (PCP). UPC is not a superset of these three languages,
but rather an attempt to distill the best characteristics of each. UPC combines
the programmability advantages of the shared memory programming paradigm
and the control over data layout and performance of the message passing
programming paradigm.
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Our work at UC Berkeley/LBNL
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| Berkeley UPC downloads since 01/May/2005 |
| Berkeley UPC Runtime: | 10116 |
| Berkeley UPC Translator: | 1844 |
| Combined Total: | 11960 |
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The goal of the Berkeley UPC compiler group is to develop a portable, high performance
implementation of UPC for large-scale multiprocessors, PC clusters, and
clusters of shared memory multiprocessors. We are actively developing
an open-source UPC compiler suite whose
goals are portability and high-performance.
There are three major components to this effort:
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Lightweight Runtime and Networking Layers: On distributed memory hardware,
references to remote shared variables usually translate into calls to a
communication library. Because of the shared
memory abstraction that it offers, UPC encourages a programming style where
remote data is accessed with a low granularity (i.e. the granularity of
an access is often the size of the primitive C types - int, float, double).
In order to be able to obtain good performance from an implementation,
it is therefore important that the overhead of accessing the underlying
communication hardware is minimized and the implementation exploits the
most efficient hardware mechanisms available.
Our group is thus developing a lightweight communication
and run-time layer for global address space programming languages.
In an effort to make our code useful to other projects, we have separated the
UPC-specific parts our runtime layer from the networking logic. If you are
implementing your own global address space language (or otherwise need a
low-level, portable networking library), you should look at our GASNet library,
which currently runs over a wide variety of high-performance networks (as well
as over any MPI 1.1 implementation), and which is also being used as the
networking layer for the Titanium language
(a high-performance parallel dialect of Java).
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Compilation techniques for explicitly parallel languages: The group
is working on developing communication optimizations to mask the latency of
network communication, aggregate communication into more efficient bulk
operations, and cache data locally. UPC allows programmers to specify memory accesses with
"relaxed " consistency semantics, which can be exploited by the compiler to hide
communication latency by overlapping communications with computation and/or
other communication.
We are implementing optimizations for the common special cases in UPC where a
programmer uses either the default, cyclic block layout for distributed arrays,
or a shared array with 'indefinite' blocksize (i.e., existing entirely on one
processor). We are also examining optimizations based on avoiding the overhead
of shared pointer manipulation when accesses are known to be local.
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Application benchmarks: The group is working on benchmarks and applications
to demonstrate the features of the UPC language and compilers, especially
targeting problems with irregular computation and communication patterns.
This effort will also allow us to determine the potential for optimizations
in UPC programs. In general,
applications with fine-grained data sharing benefit from the lightweight
communication that underlies UPC implementations, and the shared address
space model is especially appropriate when the communication is asynchronous.
Some of the research findings from this work can be found on our publications page.
Group Members
The Berkeley UPC project is funded by the DOE under based program funding from the
Office of Science,
through the DOE PModels project, and
from the Department of Defense.
Related Links
- Language Resources:
- UPC-related mailing list archives:
- Other UPC implementations: (incomplete list)
- HP UPC - for all HP-branded platforms, including Tru64, HPUX and Linux systems
- Cray UPC - for Cray X1 and future Cray vector-family platforms
- GCC UPC - for x86, SGI IRIX, Cray T3E
- IBM UPC - for IBM Blue Gene and AIX SMP's
- Michigan Tech MuPC - MPI-based reference implementation for Linux and Tru64
- Other external collaborations: (incomplete list)
- HPC Network hardware supported by Berkeley UPC, via the
GASNet communication system: (incomplete list)
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This page last modified on Tuesday, 15-Jan-2008 00:10:15 PST
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