Peking University team ports DFT ABACUS software to Huawei Kunpeng 920 processor, achieving up to 10.7x speedup
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Peking University team ports DFT ABACUS software to Huawei Kunpeng 920 processor, achieving up to 10.7x speedup

A research group led by Chen Mohan from Peking University adapted ABACUS—an open-source density functional theory (DFT) package developed in China—for the full line of Huawei Kunpeng 920 processors. Furthermore, the team optimized 19 different classes of core operators. This was reported by Huawei Computing in a publication on October 31, as learned by IT Home. The code was uploaded to the project repository on GitHub.

Density functional theory (DFT) is a primary first-principles method for studying the properties of materials such as metals and semiconductors. ABACUS was jointly developed by several institutions and has over a thousand users across more than one hundred organizations.

According to the team's data, when configuring both sides to 28 cores with 28 processes running one thread each, the Kunpeng 920 build, utilizing the SVE instruction set, showed speeds 1.3 to 3.9 times faster than a standard x86 CPU when working with a standard set of 10 material systems containing 8 to 216 atoms, including GaAs, MoS2, BaTiO3, iron, and silicon. When using the chip's matrix computation unit, the speedup reached up to 10.7 times when operating on all cores of a single node. In cases of stochastic DFT, the team recorded a speed increase of 2.8 to 3.1 times for SVE and 6.1 to 20.1 times for the build using the matrix block.

The initial step was porting, as various Kunpeng 920 models support vector instructions NEON, SVE, or SVE512, as well as a dedicated matrix block, which remain unused when using general compiler options. The team created separate toolchains: gcc with OpenMPI and OpenBLAS was used for NEON and SVE builds, while clang with HMPI and KBLAS from Huawei was used for others, and the USE_KML option was added for integration with the Kunpeng Math Library. All compiled versions passed ABACUS integration tests covering DFT for plane waves and LCAO Kohn-Sham, stochastic DFT, and DeePKS, with results matching the main implementations.

Next, the team rewrote frequently called small operators. Replacing the recursive procedure for the generalized Laguerre polynomial with an iterative recurrence allowed complexity reduction to O(n) and made it approximately eight times faster in a million-test run. Switching interpolation search to binary search reduced the average number of comparisons in a 400-entry table from about 200 to nine. Other changes included trigonometric recurrences, cycle invariant lifting, mixed-precision tuning, and memory layout, with the numerical results of each operator being re-verified.

Using automatic source code optimization in Huawei's DevKit, the team also increased the processing speed for an 8-atom high-density carbon case by 2.28 times and a 512-atom silicon case by 2.66 times on the newer Kunpeng 920 model. Huawei notes that the resulting tuning experience can be applied to other scientific software.

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The VitaAAU is an active antenna unit that integrates radio modules and antenna arrays. Huawei positions this product as the successor to the MetaAAU, which was used for sub-bands below 6 GHz. This is the first product to implement Huawei's RetinaMIMO technology in the U6GHz band. RetinaMIMO is based on three key parameters: 256 transmit and receive channels, over 1500 antenna elements, and high-speed beam scanning, which Huawei calls HBF.

The main goal of this technology is to ensure more precise control over beams and spectrum, allowing the network to handle a larger volume of traffic and provide more uniform user service. Furthermore, Huawei notes that this unit features a simplified and more eco-friendly hardware architecture.

The U6GHz band is important because it provides wide contiguous blocks of spectrum that operators can use to achieve very high throughput. Huawei reports that the VitaAAU supports peak user speeds of up to 10 Gbps and has already begun commercial operation, having been deployed in the United Arab Emirates, Hong Kong, and Macau.

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Fang Xiang, Vice President of Huawei and Director of the Wireless Network Management Committee, emphasized that artificial intelligence is transforming the nature of mobile traffic. As AI moves from the digital world into physical devices, and services become accessible to all types of terminals, networks originally designed primarily for downloads must now handle uploads on a similar scale. He suggested that the value of a network should be measured not only by the number of connections, according to Metcalfe's law, but also by the average quality of those connections.

Huawei also stated that it applies the principles of Tao's Law when designing base stations. This approach is used at the system level: the network is viewed as a single cell, which allows planning tasks to be solved compactly at the entire system level, reducing the time required for radio decision calculations and increasing overall performance.

The event will run until October 29, during which Huawei's division demonstrated a wide range of products in addition to the VitaAAU.

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Huawei states that this is the first commercial use of FDD Massive MIMO in a high-speed railway environment in China. High-speed rail networks present significant challenges for mobile coverage due to the large distance between towers, train speeds up to 350 km/h, and penetration losses caused by metal carriages.

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The laboratory stated that this step transitions Cloud Brain III into the 'construction while operating' phase. Currently, 10,000 petaflops of capacity are online, which are already being used to train large domestic models and function as a specialized AI research network for science, while the remaining capacity is still being installed.

According to the Chinese tech publication IT Home, the fully completed system is planned to reach a capacity of 16,000 petaflops, or 16 EFLOPS, and is described as the largest planned AI computing complex in China. Regarding the architecture, the laboratory's announcement only mentioned that the system utilizes an innovative domestic intelligent supernode architecture designed to eliminate data transmission bottlenecks.

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Lu Yutong, Director of the National Supercomputing Center in Shenzhen, told local media that Cloud Brain III provides the city with a solid foundation for inter-district computational connectivity and broad access to computing services. He also added that high-speed connections will extend to Hong Kong and Macau. This facility is designed as a key node of the China Computing Network (C2NET), a national pilot program that, according to the laboratory director Gao Wen, has been underway for four years.

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