Di Shan Technology AI. GPU Technology Solution: Building a New Local High end Computing Ecosystem
Overview
Against the backdrop of the global AI industry advancing into the "computing power-driven" deep-water zone, computing power has emerged as a core element determining the iteration speed of AI technologies, the efficiency of application implementation, and industrial competitiveness. As the scale of AI models grows exponentially—ranging from trillion-parameter large language models to real-time autonomous driving systems—the demand for computing power has become increasingly prominent. In this context, the independent controllability and innovative breakthroughs of computing power infrastructure have become a top priority of national science and technology strategies. As a key participant in China's AI ecosystem construction, Dishan Technology has joined hands with Germany's AragF Technology. Relying on the jointly established Sino-German AI Computing Power Joint Laboratory, the two parties have launched an all-new AI.GPU Technology Solution, which is committed to breaking the bottleneck of high-end computing power in China, building an independent, controllable, open and collaborative high-performance computing infrastructure system, and helping China seize the technological high ground in the global AI competition.
Core Positioning of the Solution: Technology Introduction + Joint Innovation + Local Empowerment
Dishan Technology's AI.GPU Technology Solution is not a simple hardware integration, but a systematic ecosystem construction project following the path of "technology introduction – joint innovation – local mass production". This path is chosen based on a profound insight into the current global computing power landscape: on one hand, internationally advanced GPU technologies dominate the high-performance computing field, but supply chain risks and export restrictions are escalating; on the other hand, China's domestic AI industry is in urgent need of a computing power base with international competitiveness and independent controllability.
Through in-depth cooperation with Germany's AragF Technology, Dishan Technology has introduced the latter's world-leading "hard power" in GPU hardware design, underlying architecture optimization, and energy efficiency management. For instance, AragF's proprietary dynamic load scheduling algorithm can improve chip utilization by 20%, while its heterogeneous memory hierarchical architecture has achieved a breakthrough in TB-level data throughput efficiency. Combined with Dishan Technology's profound understanding of China's market application scenarios and its software ecosystem adaptation capabilities, the two parties have jointly developed a localized AI computing power base characterized by high performance, high compatibility, and high cost-effectiveness.
The solution precisely addresses the current domestic pain points such as over-reliance on imported high-end GPUs, imperfect software ecosystems, and high computing power costs. Through the "introduction-digestion-reinnovation" model, it achieves technological breakthroughs and industrial implementation. For example, to tackle the stability issues of domestic AI chips in complex model training, the joint laboratory has developed an adaptive fault-tolerant mechanism, which reduces the training interruption rate to below 0.5%, reaching world-class standards. This series of innovative initiatives aims to fill the gap in the local high-end computing power ecosystem, provide solid support for the intelligent transformation of thousands of industries, and drive China's transformation from a "major computing power country" to a "strong computing power country".
Core Technical Advantages: Breaking Performance Boundaries and Reshaping Computing Power Experience
High-Performance Heterogeneous Computing Architecture: A Dual Revolution in Computing Power and Energy Efficiency
- Adopting a customized GPU core design, a single chip integrates over 50 billion transistors and supports ultra-large-scale parallel computing, which increases the training speed of large language models such as BERT by more than 3 times.
- The innovatively designed on-chip network interconnection architecture optimizes memory bandwidth and data paths, improving computing power density by 40% at the same power consumption and breaking the "power wall" limitation of traditional GPUs.
- It supports multiple precision modes including FP16, BF16, and INT8, flexibly adapting to diverse scenarios from cloud inference to edge computing. For example, in the quality inspection scenario of smart factories, the inference latency under INT8 precision is reduced to the millisecond level, meeting real-time requirements.
Full-Stack Hardware-Software Collaborative Optimization: Unlocking the "Last Mile" of Computing Power Release
- The independently developed AI computing middleware platform Zhiyu OS is deeply integrated with mainstream frameworks such as PyTorch 2.0 and TensorFlow 3.x, and provides one-click model migration tools, improving development efficiency by 50%.
- The launched AI Operator Acceleration Library conducts underlying optimization for core algorithms such as Transformer and convolutional neural networks (CNNs), improving the inference performance of typical models by 25%.
- It integrates a distributed training scheduling system, supporting cluster management of 10,000 GPU cards. In the financial risk control scenario, it has achieved the capability of processing trillion-level data in seconds, setting a new industry record.
Scenario-Oriented Vertical Optimization Capability: Making Computing Power More Industry-Savvy
- In the field of smart manufacturing, hardware-accelerated ray tracing algorithms increase the processing speed of industrial 3D point clouds by 5 times, facilitating defect detection of precision parts.
- For autonomous driving, a dedicated computing unit has been developed to accelerate the BEV perception algorithm, enabling millisecond-level fusion processing of 4D millimeter-wave radar and visual data.
- In the biopharmaceutical field, the GPU-accelerated molecular dynamics simulation platform reduces the time for protein structure analysis from months to days, accelerating the new drug R&D process.
R&D and Industrialization Layout: Full-Chain Breakthrough from Laboratory to Mass Production
Relying on the Sino-German AI Computing Power Joint Laboratory located in Shanghai, Dishan Technology is accelerating the localized implementation of AI.GPU technology:
- R&D Rhythm: The first batch of research results is expected to be released within 2026, covering next-generation GPU prototype chips, AI computing platform architectures, and key software stacks. Among them, the first mass-produced chip based on 12nm process has completed tape-out verification, with a measured computing power of 200 TFLOPS.
- Intellectual Property Goal: Over the next three years, the plan is to apply for more than 100 core technology patents covering architecture design, energy efficiency optimization, software adaptation, etc., building a "patent moat". The currently authorized patent for dynamic precision adaptive technology has filled a domestic gap.
- Standard Participation: Taking the lead in formulating 3 national standards including the *Energy Efficiency Evaluation Specification for AI Accelerator Chips*, and cooperating with IEEE to promote the internationalization of GPU interconnection protocols.
- Capacity Planning: Joining hands with domestic advanced packaging and manufacturing resources to build the first AI GPU dedicated production line in the Yangtze River Delta, with a planned annual production capacity of over 500,000 chips, forming a complete industrial chain closed loop from design to packaging and testing.
Ecosystem Co-construction and Open Cooperation: Building an AI Computing Power "Circle of Friends"
Upholding the philosophy of "openness, collaboration, and sharing", Dishan Technology is promoting the construction of a local AI computing power community:
- Cooperating with the national key laboratory AI Chip Joint Laboratory to carry out cutting-edge research on compute-in-memory and neuromorphic computing.
- Opening the Zhiyu AI Open Platform to developers, providing billion-level computing power resources, model toolchains, and scenario-specific SDKs.
- Establishing special laboratories in vertical fields such as autonomous driving and smart healthcare, and jointly developing industry-customized solutions with enterprises such as Horizon Robotics and United Imaging Healthcare.
- Attracting over 100 upstream and downstream enterprises engaged in chip design, algorithm development, and system integration, forming a collaborative innovation ecosystem.
Industrial Significance and Future Outlook: Reshaping the Global AI Computing Power Landscape
This cooperation is not only a strategic alliance between strong enterprises, but also a model of Sino-German technological collaborative innovation. A German Federal Ministry for Economic Affairs official stated at the laboratory inauguration ceremony: "This project will promote the in-depth integration of European AI technologies and Chinese application scenarios, opening up new paths for global AI development."
Its strategic significance is reflected in three aspects:
- Technological Level: Breaking the "bottleneck" of high-end GPUs and driving China to achieve independent breakthroughs in key links such as chip design and advanced manufacturing processes.
- Industrial Level: Driving the upgrading of upstream and downstream industrial chains, and it is expected to form a 100-billion-yuan industrial cluster within five years, radiating ten major industries including smart manufacturing and smart cities.
- International Influence: Gradually building a pattern of "Chinese standards + global applications" through technology export and standard cooperation. For example, projects to co-construct AI computing power infrastructure with Southeast Asian countries have already been launched.
Looking ahead, with the AI.GPU Technology Solution as the fulcrum, Dishan Technology strives to build the joint laboratory into an important global source of GPU technological innovation within five years. The goals are to achieve three major breakthroughs: first, entering the world's top three in computing power performance; second, increasing the localization rate to 80%; third, building an AI solution library covering 100 industry scenarios. With technological iteration and ecosystem improvement, China's AI industry will truly realize the vision of "using independent computing power to solve China's problems and create global value".
Computing power is productivity, and innovation is the future. Dishan Technology is writing a new chapter in the localization of China's high-end computing power, injecting surging "Chinese chip" momentum into the artificial intelligence era.