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Description
Recent breakthroughs in natural language processing, comprehension, and generation have been greatly influenced by the development of large language models. This research presents a system that employs Ascend 910 AI processors and the MindSpore framework to train a language model exceeding one trillion parameters, specifically 1.085 trillion, referred to as PanGu-{\Sigma}. This model enhances the groundwork established by PanGu-{\alpha} by converting the conventional dense Transformer model into a sparse format through a method known as Random Routed Experts (RRE). Utilizing a substantial dataset of 329 billion tokens, the model was effectively trained using a strategy called Expert Computation and Storage Separation (ECSS), which resulted in a remarkable 6.3-fold improvement in training throughput through the use of heterogeneous computing. Through various experiments, it was found that PanGu-{\Sigma} achieves a new benchmark in zero-shot learning across multiple downstream tasks in Chinese NLP, showcasing its potential in advancing the field. This advancement signifies a major leap forward in the capabilities of language models, illustrating the impact of innovative training techniques and architectural modifications.
Description
SYCL is an open, royalty-free programming standard established by the Khronos Group that facilitates heterogeneous and offload computing in modern ISO C++ by offering a unified abstraction layer where host and device code are integrated within the same C++ source file, targeting various devices such as CPUs, GPUs, FPGAs, and other accelerators. Serving as a C++ API, SYCL enhances the productivity and portability of heterogeneous computing by leveraging standard language constructs like templates, inheritance, and lambda expressions, enabling developers to effectively manage data and execution across different hardware platforms without the need for proprietary languages or extensions. Furthermore, SYCL expands upon the principles of acceleration backends like OpenCL and allows for seamless integration with other technologies, ensuring a consistent language framework, APIs, and ecosystem that simplify the processes of locating devices, managing data, and executing kernels efficiently. This adaptability makes SYCL an appealing choice for developers seeking a versatile solution in the evolving landscape of heterogeneous computing.
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Deployment
Web-Based
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Training Docs
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Vendor Details
Company Name
Huawei
Founded
1987
Country
China
Website
huawei.com
Vendor Details
Company Name
The Khronos Group
Founded
2000
Country
United States
Website
www.khronos.org
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