John Bachan is a computer systems engineer at Lawrence Berkeley National Laboratory in the Future Technologies Group. His interests span programming languages (high-level functional and systems level), to software engineering methodologies. At present his research is based in intrumentation-driven simulation of hardware for exascale. This includes cache coherency in memory hierarchies and the performance of asynchronous task-based runtimes.
John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Specification v1.0, Draft 8", Lawrence Berkeley National Laboratory Tech Report, September 26, 2018, LBNL 2001179, doi: 10.25344/S45P4X
UPC++ is a C++11 library providing classes and functions that support Partitioned Global Address Space (PGAS) programming. We are revising the library under the auspices of the DOE’s Exascale Computing Project, to meet the needs of applications requiring PGAS support. UPC++ is intended for implementing elaborate distributed data structures where communication is irregular or fine-grained. The UPC++ interfaces for moving non-contiguous data and handling memories with different optimal access methods are composable and similar to those used in conventional C++. The UPC++ programmer can expect communication to run at close to hardware speeds. The key facilities in UPC++ are global pointers, that enable the programmer to express ownership information for improving locality, one-sided communication, both put/get and RPC, futures and continuations. Futures capture data readiness state, which is useful in making scheduling decisions, and continuations provide for completion handling via callbacks. Together, these enable the programmer to chain together a DAG of operations to execute asynchronously as high-latency dependencies become satisfied.
John Bachan, Scott Baden, Dan Bonachea, Paul Hargrove, Steven Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ Programmer's Guide, v1.0-2018.9.0", Lawrence Berkeley National Laboratory Tech Report, September 26, 2018, LBNL 2001180, doi: 10.25344/S49G6V
UPC++ is a C++11 library that provides Partitioned Global Address Space (PGAS) programming. It is designed for writing parallel programs that run efficiently and scale well on distributed-memory parallel computers. The PGAS model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. However, PGAS also provides access to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ provides numerous methods for accessing and using global memory. In UPC++, all operations that access remote memory are explicit, which encourages programmers to be aware of the cost of communication and data movement. Moreover, all remote-memory access operations are by default asynchronous, to enable programmers to write code that scales well even on hundreds of thousands of cores.
Scott B. Baden, Paul H. Hargrove, Hadia Ahmed, John Bachan, Dan Bonachea, Steve Hofmeyr, Mathias Jacquelin, Amir Kamil, Brian van Straalen, "UPC++ and GASNet-EX: PGAS Support for Exascale Applications and Runtimes", The International Conference for High Performance Computing, Networking, Storage and Analysis (SC'18), November 13, 2018,
Lawrence Berkeley National Lab is developing a programming system to support HPC application development using the Partitioned Global Address Space (PGAS) model. This work is driven by the emerging need for adaptive, lightweight communication in irregular applications at exascale. We present an overview of UPC++ and GASNet-EX, including examples and performance results.
GASNet-EX is a portable, high-performance communication library, leveraging hardware support to efficiently implement Active Messages and Remote Memory Access (RMA). UPC++ provides higher-level abstractions appropriate for PGAS programming such as: one-sided communication (RMA), remote procedure call, locality-aware APIs for user-defined distributed objects, and robust support for asynchronous execution to hide latency. Both libraries have been redesigned relative to their predecessors to meet the needs of exascale computing. While both libraries continue to evolve, the system already demonstrates improvements in microbenchmarks and application proxies.