arXiv subjects

Weile Wei

Publications and source records attributed to Weile Wei.

4 recordsLinked to original sources

arXiv2021

A Case Study of LLVM-Based Analysis for Optimizing SIMD Code Generation

This paper presents a methodology for using LLVM-based tools to tune the DCA++ (dynamical clusterapproximation) application that targets the new ARM A64FX processor. The goal is to describethe changes required for the new architecture and generate efficient single instruction/multiple data(SIMD) instructions that target the new Scalable Vector Extension instruction set. During manualtuning, the authors used the LLVM tools to improve code parallelization by using OpenMP SIMD,refactored the code and applied transformation that enabled SIMD optimizations, and ensured thatthe correct libraries were used to achieve optimal performance. By applying these code changes, codespeed was increased by 1.98X and 78 GFlops were achieved on the A64FX processor. The authorsaim to automatize parts of the efforts in the OpenMP Advisor tool, which is built on top of existingand newly introduced LLVM tooling.

cs.DC↗

arXiv2021

Memory Reduction using a Ring Abstraction over GPU RDMA for Distributed Quantum Monte Carlo Solver

Scientific applications that run on leadership computing facilities often face the challenge of being unable to fit leading science cases onto accelerator devices due to memory constraints (memory-bound applications). In this work, the authors studied one such US Department of Energy mission-critical condensed matter physics application, Dynamical Cluster Approximation (DCA++), and this paper discusses how device memory-bound challenges were successfully reduced by proposing an effective "all-to-all" communication method -- a ring communication algorithm. This implementation takes advantage of acceleration on GPUs and remote direct memory access (RDMA) for fast data exchange between GPUs. Additionally, the ring algorithm was optimized with sub-ring communicators and multi-threaded support to further reduce communication overhead and expose more concurrency, respectively. The computation and communication were also analyzed by using the Autonomic Performance Environment for Exascale (APEX) profiling tool, and this paper further discusses the performance trade-off for the ring algorithm implementation. The memory analysis on the ring algorithm shows that the allocation size for the authors' most memory-intensive data structure per GPU is now reduced to 1/p of the original size, where p is the number of GPUs in the ring communicator. The communication analysis suggests that the distributed Quantum Monte Carlo execution time grows linearly as sub-ring size increases, and the cost of messages passing through the network interface connector could be a limiting factor.

cs.DC↗

arXiv2020

Performance Analysis of a Quantum Monte Carlo Application on Multiple Hardware Architectures Using the HPX Runtime

This paper describes how we successfully used the HPX programming model to port the DCA++ application on multiple architectures that include POWER9, x86, ARM v8, and NVIDIA GPUs. We describe the lessons we can learn from this experience as well as the benefits of enabling the HPX in the application to improve the CPU threading part of the code, which led to an overall 21% improvement across architectures. We also describe how we used HPX-APEX to raise the level of abstraction to understand performance issues and to identify tasking optimization opportunities in the code, and how these relate to CPU/GPU utilization counters, device memory allocation over time, and CPU kernel-level context switches on a given architecture.

cs.DC↗

arXiv2019

An Introduction to hpxMP: A Modern OpenMP Implementation Leveraging HPX, An Asynchronous Many-Task System

Asynchronous Many-task (AMT) runtime systems have gained increasing acceptance in the HPC community due to the performance improvements offered by fine-grained tasking runtime systems. At the same time, C++ standardization efforts are focused on creating higher-level interfaces able to replace OpenMP or OpenACC in modern C++ codes. These higher level functions have been adopted in standards conforming runtime systems such as HPX, giving users the ability to simply utilize fork-join parallelism in their own codes. Despite innovations in runtime systems and standardization efforts users face enormous challenges porting legacy applications. Not only must users port their own codes, but often users rely on highly optimized libraries such as BLAS and LAPACK which use OpenMP for parallization. Current efforts to create smooth migration paths have struggled with these challenges, especially as the threading systems of AMT libraries often compete with the treading system of OpenMP. To overcome these issues, our team has developed hpxMP, an implementation of the OpenMP standard, which utilizes the underlying AMT system to schedule and manage tasks. This approach leverages the C++ interfaces exposed by HPX and allows users to execute their applications on an AMT system without changing their code. In this work, we compare hpxMP with Clang's OpenMP library with four linear algebra benchmarks of the Blaze C++ library. While hpxMP is often not able to reach the same performance, we demonstrate viability for providing a smooth migration for applications but have to be extended to benefit from a more general task based programming model.

cs.DC↗