Blis software

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Rich support for the complex domain. BLIS operations are developed and expressed in their most general form, which is typically in the complex domain. These formulations then simplify elegantly down to the real domain, with conjugations becoming no-ops.

Unlike the BLAS, all input operands in BLIS that allow transposition and conjugate-transposition also support conjugation without transposition , which obviates the need for thread-unsafe workarounds. Also, where applicable, both complex symmetric and complex Hermitian forms are supported.

BLAS omits some complex symmetric operations, such as symv , syr , and syr2. Another great example of BLIS serving as a portability lever is its implementation of the 1m method for complex matrix multiplication, a novel mechanism of providing high-performance complex level-3 operations using only real domain microkernels. This new innovation guarantees automatic level-3 support in the complex domain even when the kernel developers entirely forgo writing complex kernels. Advanced multithreading support.

BLIS allows multiple levels of symmetric multithreading for nearly all level-3 operations. This means that matrices may be partitioned in multiple dimensions simultaneously to attain scalable, high-performance parallelism on multicore and many-core architectures.

The key to this innovation is a thread-specific control tree infrastructure which encodes information about the logical thread topology and allows threads to query and communicate data amongst one another.

BLIS also employs so-called "quadratic partitioning" when computing dimension sub-ranges for each thread, so that arbitrary diagonal offsets of structured matrices with unreferenced regions are taken into account to achieve proper load balance. More recently, BLIS introduced a runtime abstraction to specify parallelism on a per-call basis, which is useful for applications that want to handle most of the parallelism. Ease of use. The BLIS framework, and the library of routines it generates, are easy to use for end users, experts, and vendors alike.

Or, one may adjust or write their application to take advantage of new BLIS functionality such as generalized storage formats or additional complex operations by calling one of BLIS's native APIs directly. Objects are relatively lightweight structs and passed by address, which helps tame function calling overhead. Multilayered API and exposed kernels. The BLIS framework exposes its implementations in various layers, allowing expert developers to access exactly the functionality desired.

This layered interface includes that of the lowest-level kernels, for those who wish to bypass the bulk of the framework. Optimizations can occur at various levels, in part thanks to exposed packing and unpacking facilities, which by default are highly parameterized and flexible. Functionality that grows with the community's needs.

Furthermore, the framework is extensible, allowing developers to leverage existing components to support new operations as they are identified. If such operations require new kernels for optimal efficiency, the framework and its APIs will be adjusted and extended accordingly. Code re-use. Auto-generation approaches to achieving the aforementioned goals tend to quickly lead to code bloat due to the multiple dimensions of variation supported: operation i.

These "brute force" approaches often consider and optimize each operation or case combination in isolation, which is less than ideal when the goal is to provide entire libraries. BLIS was designed to be a complete framework for implementing basic linear algebra operations, but supporting this vast amount of functionality in a manageable way required a holistic design that employed careful abstractions, layering, and recycling of generic highly parameterized codes, subject to the constraint that high performance remain attainable.

BLIS was designed with the hope of one day allowing computation on real and complex operands within the same operation. Similarly, we wanted to allow mixing operands' numerical domains, floating-point precisions, or both domain and precision, and to optionally compute in a precision different than one or both operands' storage precisions.

This feature has been implemented for the general matrix multiplication gemm operation, providing different possible type combinations, which, when combined with existing transposition, conjugation, and storage parameters, enables 55, different gemm use cases.

There are a few ways to download BLIS. We list the most common four ways below. We highly recommend using either Option 1 or 2. Otherwise, we recommend Option 3 over Option 4 so your compiler can perform optimizations specific to your hardware.

Download a source repository with git clone. Generally speaking, we prefer using git clone to clone a git repository. Having a repository allows the user to periodically pull in the latest changes and quickly rebuild BLIS whenever they wish. Also, implicit in cloning a repository is that the repository defaults to using the master branch, which contains the latest "stable" commits since the most recent release. This is in contrast to Option 3 in which the user is opting for code that may be slightly out of date.

Generally speaking, it will amount to executing the following command in your terminal shell:. Download a source repository via a zip file. If you are uncomfortable with using git but would still like the latest stable commits, we recommend that you download BLIS as a zip file. In order to download a zip file of the BLIS source distribution, please click on the green button above the file listing near the top of this page.

This should reveal a link for downloading the zip file. Alternatively, if you would like to stick to the code that is included in official releases, you may download either a tarball or zip file of any of BLIS's previous tagged releases.

We consider this option to be less than ideal for most people since it will likely mean you miss out on the latest bugfix or feature commits in contrast to Options 1 or 2 , and you also will not be able to update your code with a simple git pull command in contrast to Option 1. Download a binary package specific to your OS. Please see the External Packages section below for more information.

NOTE: This section assumes you've either cloned a BLIS source code repository via git , downloaded the latest source code via a zip file, or downloaded the source code for a tagged version releaseOptions 1, 2, or 3, respectively, as discussed in the previous section.

If you just want to build a sequential not parallelized version of BLIS in a hurry and come back and explore other topics later, you can configure and build BLIS as follows:. And if you would like to install BLIS to the directory specified to configure via the --prefix option, run the install target:. Please read the output of.

The BLIS source distribution provides example code in the examples directory. Either directory contains several files, each containing various pieces of code that exercise core functionality of the BLIS API in question object or typed.

These example files should be thought of collectively like a tutorial, and therefore it is recommended to start from the beginning the file that starts in You can also run make clean.

The local Makefile assumes that you've already configured and built but not necessarily installed BLIS two directories up, in.. Once the executable files have been built, we recommend reading the code and the corresponding executable output side by side.

This will help you see the effects of each section of code. This tutorial is not exhaustive or complete; several object API functions were omitted mostly for brevity's sake and thus more examples could be written. All documentation is formatted in markdown and included in the BLIS source distribution usually in the docs directory.

Slightly longer descriptions of each document may be found via in the project's wiki section. Build System. This document covers the basics of configuring and building BLIS libraries, as well as related topics. Here we document the object API. Hardware Support. This document maintains a table of supported microarchitectures. This document describes how to use the multithreading features of BLIS. This document provides an overview of BLIS's mixed-datatype functionality and provides a brief example of how to take advantage of this new code.

This document reports empirically measured performance of a representative set of level-3 operations on a variety of hardware architectures, as implemented within BLIS and other BLAS libraries for all four of the standard floating-point datatypes.