Berkeley UPC - Unified Parallel C

The UPC Language

About this UPC program About this UPC program

 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:

• An explicitly parallel execution model
• A shared address space
• Synchronization primitives and a memory consistency model
• Parallel utility libraries

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.

Our work in the LBNL Pagoda Group

Berkeley UPC downloads since 01/May/2005 Berkeley UPC Runtime Source 280010 Berkeley UPC Translator Source 49369 Berkeley UPC Cygwin Binary 3386 Berkeley UPC MacOS Binary 10393 Combined Total 343158

The Berkeley UPC compiler suite is currently maintained primarily by the Pagoda Project in the CLaSS Group at Lawrence Berkeley National Laboratory. The goal of the Berkeley UPC team is to develop a portable, high performance implementation of UPC for large-scale multiprocessors, PC clusters, and clusters of shared memory multiprocessors.  We are developing an open-source UPC compiler suite whose goals are portability and high-performance.

The major components of our project are:

• 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 has thus developed 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). Additionally, several external projects have adopted GASNet for their PGAS networking requirements.

• 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.

• 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.

• Active Testing: UPC programs can have classes of bugs not possible in a programming model such as MPI. In order to help find and correct data races, deadlocks and other programming errors, we are working on UPC Thrille.

• Dynamic Tasking: UPC Task Library is a simple and effective way of adding task parallelism to SPMD programs. It provides a high-level API that abstracts concurrent task management details and a dynamic load balancing mechanism.

Some of the research findings from these areas of work can be found on our publications page.

UPC Compiler Infrastructure

There are multiple compiler infrastructures available for use with the Berkeley UPC runtime and compiler driver: two source-to-source translators (based on LLVM and Open64) and two compilers (based on LLVM and GCC). For details please see the download page.

All compilers have been tested using the same procedure and our recommendations in terms of robustness and performance are below.

1. Clang UPC2C source-to-source (CUPC2C) translator
   We consider this to be the most robust option.
   Though results will vary with your choice of a backend C compiler, this option is likely to result in best performance.
   Developed by INTREPID Technology Inc and Tactical Computing Laboratories.
2. Clang UPC source-to-binary (CUPC) compiler
   We consider this to be a less-portable alternative to CUPC2C.
   The performance is determined by the code generation of LLVM 3 (no option to use other backend compilers).
   Developed by INTREPID Technology Inc.
3. Open64-based source-to-source UPC-to-C (BUPC) translator
   This is the default compiler, hosted as a netcompile service by the Pagoda Project at Lawrence Berkeley National Laboratory.
   Performance is determined by the backend C compiler.
   Developed by the CLaSS group at LBNL.
4. GNU UPC source-to-binary (GUPC) compiler
   We consider this option to be generally robust.
   The performance is determined by the code generation of GCC 5.2 (no option to use other backend compilers).
   Developed by INTREPID Technology Inc.

All of the compiler options above use the Berkeley UPC runtime and compiler driver, which is available on the download page.

Related Links

• Language Resources:
  • UPC Community Site - documentation and collaboration website for UPC (archived)
  • UPC Language Specification Working Group - UPC specification development
  • Titanium Language - Java-based language with similar properties to UPC
  • UPC++ Library - C++ PGAS communication library with similar properties to UPC
  • Co-Array Fortran Language, Rice CAF 2.0 - Fortran-based language with similar properties to UPC
• UPC-related mailing list archives:
  • Berkeley UPC user help list: Berkeley UPC Users [current]      Berkeley UPC Users [before May 2010]     
  • Announcements: UPC Community Announcements [archived]
• Other UPC implementations: (incomplete list)
  
  • HP UPC - for all HP-branded platforms, including Tru64, HPUX and Linux systems
  • Cray UPC - for Cray X1, XT, XE, XK, XC and future Cray platforms
  • SGI UPC - for Altix UV systems
  • GNU UPC - for Linux, MacOSX, SGI IRIX, Cray T3E
  • IBM UPC - for IBM Blue Gene and AIX SMP's
  • Clang UPC - for Linux, MacOSX and others
  • Michigan Tech MuPC - MPI-based reference implementation for Linux and Tru64
• Other past and present collaborations: (incomplete list)
  
  • HipMer - A High performance distributed memory assembler for big genomic data, using UPC and UPC++
  • Berkeley Lab Checkpoint/Restart (BLCR) - transparent checkpoint/restart of Berkeley UPC applications
  • Perforce Software - TotalView debugger, supports Berkeley UPC
  • Allinea Software - Allinea DDT debugger, supports Berkeley UPC
  • University of Florida - Parallel Performance Wizard performance analysis tool that uses the Berkeley UPC GASP profiling interface
  • George Washington University - UPC-IO, UPC testing and benchmarking suites
• HPC Network hardware supported by Berkeley UPC, via the GASNet communication system: (incomplete list)
  
  • HPE Cray EX Series (ofi)
  • Cray XC Series (aries)
  • IBM Parallel Active Message Interface (pami) - deprecated
  • InfiniBand: OpenFabrics/OpenIB Verbs (ibv)
  • Any MPI-1.1 compliant system (mpi) - portable support
  • Any TCP/IP Ethernet (udp) - portable support