computer science

OpenBLAS

OpenBLAS is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand OpenBLAS rather than just read about it. In short: OpenBLAS is an open-source implementation of the BLAS (Basic Linear Algebra Subprograms) and LAPACK APIs with many hand-crafted optimizations for specific processor types. It is developed at the Lab of Parallel Software and Computational Science, ISCAS.

Key takeaways

OpenBLAS belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect OpenBLAS to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of OpenBLAS from memory before moving on to harder problems.

Reference excerpt

OpenBLAS is an open-source implementation of the BLAS (Basic Linear Algebra Subprograms) and LAPACK APIs with many hand-crafted optimizations for specific processor types. It is developed at the Lab of Parallel Software and Computational Science, ISCAS. OpenBLAS adds optimized implementations of linear algebra kernels for several processor architectures, including Intel Sandy Bridge and Loongson. It claims to achieve performance comparable to the Intel MKL. On machines that support the AVX2 instruction set, OpenBLAS can achieve similar performance to MKL, but there are currently almost no open source libraries comparable to MKL on CPUs with the AVX512 instruction set. OpenBLAS is a fork of GotoBLAS2, which was created by Kazushige Goto at the Texas Advanced Computing Center.

History and present OpenBLAS was developed by the parallel software group led by Professor Yunquan Zhang from the Chinese Academy of Sciences. OpenBLAS was initially only for the Loongson CPU platform. Dr. Xianyi Zhang contributed a lot of work. Since GotoBLAS was abandoned, the successor OpenBLAS is now developed as an open source BLAS library for multiple platforms, including x86, ARMv8, MIPS, and RISC-V platforms, and is respected for its excellent portability. The parallel software group is modernizing OpenBLAS to meet current computing needs. For example, OpenBLAS's level-3 computations were primarily optimized for large and square matrices (often considered as regular-shaped matrices). And now irregular-shaped matrix multiplication are also supported, such as tall and skinny matrix multiplication (TSMM), which supports faster deep learning calculations on the CPU. TSMM is one of the core calculations in deep learning operations. Besides this, the compact function and small GEMM will also be supported by OpenBLAS.

Worked examples

Example 1 — a first encounter with OpenBLAS

Start with the simplest possible case. Write down what OpenBLAS claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to OpenBLAS before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about OpenBLAS ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of OpenBLAS

In research: OpenBLAS appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses OpenBLAS in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: OpenBLAS is common in secondary-school and first-year university syllabi. It links to neighbouring topics Numerical linear algebra, Numerical software, Software using the BSD license, so understanding it makes those chapters shorter.
In everyday life: Look for OpenBLAS outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study OpenBLAS in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what OpenBLAS means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain OpenBLAS out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is OpenBLAS in simple terms?

Why does OpenBLAS matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study OpenBLAS?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on OpenBLAS.