Roofline Model Toolkit: A Practical Tool for Architectural and Program Analysis

Lo, Yu Jung; Williams, Samuel; Straalen, Brian Van; Ligocki, Terry J.; Cordery, Matthew J.; Wright, Nicholas J.; Hall, Mary; Oliker, Leonid

doi:10.1007/978-3-319-17248-4_7

Cited by 74 publications

(34 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is employed for performance analysis in various application domains: digital signal processing, e.g., Spiral [52], sparse/dense linear algebra [64,67], and La ice Boltzmann Magnetohydrodynamics (LBMHD) [64]. e Empirical Roo ine Tool (ERT) [46], included into Intel Advisor tool, automates measuring the target machine characteristics. ERT automatically generates Roo ine data including the maximum bandwidth for various levels of the memory hierarchy which are obtained by testing a variety of micro-kernels 5 .…”

Section: Roo Ine Performance Modelsmentioning

confidence: 99%

A parallel sparse tensor benchmark suite on CPUs and GPUs

Lakshminarasimhan

et al. 2020

Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

View full text Add to dashboard Cite

Tensor computations present signi cant performance challenges that impact a wide spectrum of applications ranging from machine learning, healthcare analytics, social network analysis, data mining to quantum chemistry and signal processing. E orts to improve the performance of tensor computations include exploring data layout, execution scheduling, and parallelism in common tensor kernels. is work presents a benchmark suite for arbitrary-order sparse tensor kernels using state-of-the-art tensor formats: coordinate (COO) and hierarchical coordinate (HiCOO) on CPUs and GPUs. It presents a set of reference tensor kernel implementations that are compatible with real-world tensors and power law tensors extended from synthetic graph generation techniques. We also propose Roo ine performance models for these kernels to provide insights of computer platforms from sparse tensor view.

show abstract

Section: Roo Ine Performance Modelsmentioning

confidence: 99%

A parallel sparse tensor benchmark suite on CPUs and GPUs

Lakshminarasimhan

et al. 2020

Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

View full text Add to dashboard Cite

show abstract

“…We measured the maximum bandwidth for the various levels of the memory and the maximum flop‐rate on a Blue Waters XE node using the Empirical Roofline Tool (ERT) version 1.1.0. Three types of compilers were used with the ERT as follows: GNU compiler: gcc/4.9.3 and gcc/6.3.0 Cray compiler: cce/8.5.8 PGI compiler: pgi/17.5.0. …”

Section: Roofline Measurements Of a Blue Waters Xe Nodementioning

confidence: 99%

Roofline analysis with Cray performance analysis tools (CrayPat) and roofline‐based performance projections for a future architecture

Kwack

Arnold

Mendes

et al. 2018

Concurrency and Computation

View full text Add to dashboard Cite

Summary The roofline analysis model is a visually intuitive performance model used to understand hardware performance limitations as well as potential benefits of optimizations for science and engineering applications. Intel Advisor has provided a useful roofline analysis feature since its version 2017 update 2, but it is not widely compatible with other compilers and chip‐architectures. As an alternative, we have employed Cray Performance Analysis Tools (CrayPat) that are more flexible for multiple compilers and architectures. First, we present our procedure for measuring a reliable computational intensity for roofline analysis. We performed several numerical studies for validation via manually derived reference data as well as data from Intel Advisor. Second, we provide roofline analysis results on Blue Waters for several HPC benchmarks and sparse linear algebra libraries. In addition, we present an example of roofline‐based performance projection for a future system.

show abstract

“…It can also incorporate communication (i.e., message passing) overhead, which is not the scope of our research. Lo et al [14] introduced in 2014 the "Empirical Roofline Toolkit," (ERT) which aims at automatically generating hardware descriptions for Roofline analysis. They do not support automatic topology detection and their use of compiler-generated loops introduces an element of uncertainty.…”

Section: Related Workmentioning

confidence: 99%

Kerncraft: A Tool for Analytic Performance Modeling of Loop Kernels

Hammer

Eitzinger

Hager

et al. 2017

Tools for High Performance Computing 2016

View full text Add to dashboard Cite

Achieving optimal program performance requires deep insight into the interaction between hardware and software. For software developers without an indepth background in computer architecture, understanding and fully utilizing modern architectures is close to impossible. Analytic loop performance modeling is a useful way to understand the relevant bottlenecks of code execution based on simple machine models. The Roofline Model and the Execution-Cache-Memory (ECM) model are proven approaches to performance modeling of loop nests. In comparison to the Roofline model, the ECM model can also describes the single-core performance and saturation behavior on a multicore chip. We give an introduction to the Roofline and ECM models, and to stencil performance modeling using layer conditions (LC). We then present Kerncraft, a tool that can automatically construct Roofline and ECM models for loop nests by performing the required code, data transfer, and LC analysis. The layer condition analysis allows to predict optimal spatial blocking factors for loop nests. Together with the models it enables an ab-initio estimate of the potential benefits of loop blocking optimizations and of useful block sizes. In cases where LC analysis is not easily possible, Kerncraft supports a cache simulator as a fallback option. Using a 25-point long-range stencil we demonstrate the usefulness and predictive power of the Kerncraft tool.

show abstract

Roofline Model Toolkit: A Practical Tool for Architectural and Program Analysis

Cited by 74 publications

References 6 publications

A parallel sparse tensor benchmark suite on CPUs and GPUs

A parallel sparse tensor benchmark suite on CPUs and GPUs

Roofline analysis with Cray performance analysis tools (CrayPat) and roofline‐based performance projections for a future architecture

Kerncraft: A Tool for Analytic Performance Modeling of Loop Kernels

Contact Info

Product

Resources

About