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Graham, Richard L

Publications and source records attributed to Graham, Richard L.

13 records
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DOE OSTI2013

Optimizing Blocking and Nonblocking Reduction Operations for Multicore Systems: Hierarchical Design and Implementation

Many scientific simulations, using the Message Passing Interface (MPI) programming model, are sensitive to the performance and scalability of reduction collective operations such as MPI Allreduce and MPI Reduce. These operations are the most widely used abstractions to perform mathematical operations over all processes that are part of the simulation. In this work, we propose a hierarchical design to implement the reduction operations on multicore systems. This design aims to improve the efficiency of reductions by 1) tailoring the algorithms and customizing the implementations for various communication mechanisms in the system 2) providing the ability to configure the depth of hierarchy to match the system architecture, and 3) providing the ability to independently progress each of this hierarchy. Using this design, we implement MPI Allreduce and MPI Reduce operations (and its nonblocking variants MPI Iallreduce and MPI Ireduce) for all message sizes, and evaluate on multiple architectures including InfiniBand and Cray XT5. We leverage and enhance our existing infrastructure, Cheetah, which is a framework for implementing hierarchical collective operations to implement these reductions. The experimental results show that the Cheetah reduction operations outperform the production-grade MPI implementations such as Open MPI default, Cray MPI, and MVAPICH2, demonstrating its efficiency, flexibility and portability. On Infini- Band systems, with a microbenchmark, a 512-process Cheetah nonblocking Allreduce and Reduce achieves a speedup of 23x and 10x, respectively, compared to the default Open MPI reductions. The blocking variants of the reduction operations also show similar performance benefits. A 512-process nonblocking Cheetah Allreduce achieves a speedup of 3x, compared to the default MVAPICH2 Allreduce implementation. On a Cray XT5 system, a 6144-process Cheetah Allreduce outperforms the Cray MPI by 145%. The evaluation with an application kernel, Conjugate Gradient solver, shows that the Cheetah reductions speeds up total time to solution by 195%, demonstrating the potential benefits for scientific simulations.

Gorentla Venkata, Manjunath↗
DOE OSTI2012

HERCULES: A Pattern Driven Code Transformation System

New parallel computers are emerging, but developing efficient scientific code for them remains difficult. A scientist must manage not only the science-domain complexity but also the performance-optimization complexity. HERCULES is a code transformation system designed to help the scientist to separate the two concerns, which improves code maintenance, and facilitates performance optimization. The system combines three technologies, code patterns, transformation scripts and compiler plugins, to provide the scientist with an environment to quickly implement code transformations that suit his needs. Unlike existing code optimization tools, HERCULES is unique in its focus on user-level accessibility. In this paper we discuss the design, implementation and an initial evaluation of HERCULES.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Open MPI for Cray XE/XK Systems

Open MPI provides an implementation of the MPI standard supporting communications over a range of high-performance network interfaces. Recently, ORNL and LANL have collaborated on creating a port of Open MPI for Gemini, the network interface for Cray XE and XK systems. In this paper, we present our design and implementation of Open MPI's point-to-point and collective operations for Gemini, and techniques we employ to provide good scaling, and performance characteristics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Assessing the Performance and Scalability of a Novel Multilevel K-Nomial Allgather on CORE-Direct Systems

In this paper, we propose a novel allgather algorithm, Reindexed Recursive K-ing (RRK), which leverages flexibility in the algorithm's tree topology and ability to make asynchronous progress coupled with Core-Direct communication offload capability to optimize the MPI-Allgather for Core-Direct enabled systems. In particular, the RRK introduces a reindexing scheme which ensures contiguous data transfers while adding only a single additional send and receive operation for any radix, k, or communicator size, N. This allows us to improve algorithm scalability by avoiding the use of a scatter/gather elements (SGE) list on InfiniBand networks. The implementations of the RRK algorithm and its evaluation shows that it performs and scales well on Core-Direct systems for a wide range of message sizes and various communicator configurations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Experiences with High-Level Programming Directives for Porting Applications to GPUs

HPC systems now exploit GPUs within their compute nodes to accelerate program performance. As a result, high-end application development has become extremely complex at the node level. In addition to restructuring the node code to exploit the cores and specialized devices, the programmer may need to choose a programming model such as OpenMP or CPU threads in conjunction with an accelerator programming model to share and manage the difference node resources. This comes at a time when programmer productivity and the ability to produce portable code has been recognized as a major concern. In order to offset the high development cost of creating CUDA or OpenCL kernels, directives have been proposed for programming accelerator devices, but their implications are not well known. In this paper, we evaluate the state of the art accelerator directives to program several applications kernels, explore transformations to achieve good performance, and examine the expressiveness and performance penalty of using high-level directives versus CUDA. We also compare our results to OpenMP implementations to understand the benefits of running the kernels in the accelerator versus CPU cores.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

The Impact of a Fault Tolerant MPI on Scalable Systems Services and Applications

Exascale targeted scientific applications must be prepared for a highly concurrent computing environment where failure will be a regular event during execution. Natural and algorithm-based fault tolerance (ABFT) techniques can often manage failures more efficiently than traditional checkpoint/restart techniques alone. Central to many petascale applications is an MPI standard that lacks support for ABFT. The Run-Through Stabilization (RTS) proposal, under consideration for MPI 3, allows an application to continue execution when processes fail. The requirements of scalable, fault tolerant MPI implementations and applications will stress the capabilities of many system services. System services must evolve to efficiently support such applications and libraries in the presence of system component failures. This paper discusses how the RTS proposal impacts system services, highlighting specific requirements. Early experimentation results from Cray systems at ORNL using prototype MPI and runtime implementations are presented. Additionally, this paper outlines fault tolerance techniques targeted at leadership class applications.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

The Co Design Architecture for Exascale Systems, a Novel Approach for Scalable Designs

High performance computing (HPC) has begun scaling beyond the Petaflop range towards the Exaflop (1000 Petaflops) mark. One of the major concerns throughout the development toward such performance capability is scalability both at the system level and the application layer. In this paper we present a novel approach for a new design concept the Co Design approach with enables a tighter development of both the application communication libraries and the underlying hardware interconnect solution in order to overcome scalability issues and to enable a more efficient design approach towards Exascale computing. We have suggested a new application programing interface and have demonstrated a 50x improvement of performance and scalability increases.

Kagan, Michael↗