Achieve Optimal Performance with Intel Parallel Studio XE 2015

Achieve Optimal Performance with Intel Parallel Studio XE 2015

Table of Contents

1. Introduction
2. Overview of Studio XE
3. New Features in Studio XE 2015
   • Explicit Vectorization
   • OpenMP 4.0 Support
   • AVX 512 Vectorization
4. Benefits of Vectorization
5. Vectorization in C++ and Other Languages
6. Simplifying Parallel Code
7. Writing Code Closer to Scientific Equations
8. Shipping and Availability

Introduction

In this article, we will explore the latest version of Studio XE, a suite of tools, compilers, libraries, and analysis tools offered by Intel. We will discuss the new features in Studio XE 2015 and the benefits they bring to high-performance computing (HPC). Specifically, we will focus on explicit vectorization, open MP 4.0 support, and AVX 512 vectorization. Additionally, we will examine the advantages of vectorization, especially in the context of C++ and other programming languages. Furthermore, we will explore how Studio XE simplifies parallel code and enables scientists to write code that closely resembles their scientific equations. Finally, we will discuss the availability and shipping details of Studio XE 2015.

Studio XE: Empowering High-Performance Computing

Studio XE is an all-encompassing suite of tools and libraries designed to enhance performance in high-performance computing. It includes compilers, analysis tools, and libraries that are popular among HPC developers. With each new version, Studio XE continues to innovate and provide developers with powerful features and capabilities.

New Features in Studio XE 2015

Explicit Vectorization

One of the most exciting features in Studio XE 2015 is explicit vectorization. This feature allows developers to explicitly instruct the compiler to use SIMD (Single Instruction, Multiple Data) instructions. With explicit vectorization, developers can take advantage of the full potential of vectorization and significantly improve performance. This new programming style eliminates the need for the compiler to make decisions about vectorization, offering developers more control over the optimization process.

OpenMP 4.0 Support

Studio XE 2015 also introduces support for OpenMP 4.0, a widely used programming model for parallel computing. OpenMP 4.0 brings together tasking, vectorization, and offload capabilities, enabling developers to harness the power of parallelism and vectorization simultaneously. This combination results in a highly efficient and effective approach to optimize code.

AVX 512 Vectorization

Another notable addition to Studio XE 2015 is AVX 512 vectorization. With AVX 512, developers can perform vector operations on a larger Scale, allowing for up to 16 single precision or 8 double precision calculations at a time. This significant increase in vector length provides substantial performance improvements across a wide range of applications.

Benefits of Vectorization

Vectorization offers several key benefits for developers. First and foremost, it allows for significant performance improvements by utilizing the full processing power of modern CPUs. By performing multiple calculations simultaneously, vectorization can speed up computations by a factor of up to 16 or more. This acceleration is particularly beneficial for computationally intensive tasks commonly found in scientific simulations, data analysis, and machine learning algorithms.

Moreover, vectorization extends beyond traditional Fortran loops and is now applicable to a variety of programming languages, including C++ and others. This expansion enables developers to optimize their code regardless of the language used, unlocking performance gains for a wider range of applications.

Simplifying Parallel Code

Traditionally, writing parallel code required rewriting algorithms and structures to conform to parallel computing paradigms. With Studio XE 2015, the process is Simplified. Developers can write parallel code that closely resembles their scientific equations, thanks to the capabilities introduced by OpenMP 4.0. By specifying directives such as parallelize and vectorize, developers can instruct the compiler to automatically transform their code into an optimized parallel version. This approach not only increases code readability but also improves performance, making parallel programming more accessible and efficient.

Writing Code Closer to Scientific Equations

Scientists and researchers often struggle to Translate their scientific equations into efficient parallel code. Studio XE 2015 addresses this challenge by allowing developers to write code that closely resembles their mathematical representations. By collapsing loops and combining parallel and vector directives, developers can create code that mirrors the original equations. This approach not only makes the code more readable and maintainable but also ensures high-performance execution.

Shipping and Availability

Studio XE 2015 is available for immediate shipping. Customers can download the latest version from Intel's website or request an evaluation copy. The new features and capabilities offered by Studio XE 2015 make it an essential tool for developers in the field of high-performance computing.

Highlights

• Studio XE is an all-in-one suite of tools, compilers, libraries, and analysis tools for high-performance computing.
• Studio XE 2015 introduces explicit vectorization, allowing developers to have more control over optimization.
• OpenMP 4.0 support in Studio XE 2015 enables simultaneous parallelization and vectorization for enhanced performance.
• AVX 512 vectorization in Studio XE 2015 provides significant speed-ups by performing multiple calculations simultaneously.
• Vectorization offers performance improvements for a wide range of applications, including scientific simulations and machine learning algorithms.
• Studio XE 2015 simplifies parallel code writing, allowing developers to write code closer to their scientific equations.
• Studio XE 2015 is available for immediate download and evaluation.

FAQ

Q: Can I use Studio XE for languages other than Fortran? A: Yes, Studio XE supports a variety of programming languages, including C and C++.

Q: Is explicit vectorization useful for all types of code? A: Explicit vectorization is most effective for computationally intensive code that can benefit from parallel execution.

Q: Does Studio XE 2015 support older versions of OpenMP? A: Yes, Studio XE 2015 supports multiple versions of OpenMP, including OpenMP 4.0.

Q: How can I get started with Studio XE 2015? A: You can download an evaluation copy of Studio XE 2015 from Intel's website and explore its features and capabilities.