{"id":148726,"date":"2023-10-11T17:30:10","date_gmt":"2023-10-11T08:30:10","guid":{"rendered":"http:\/\/ee.presscat.kr\/?post_type=research-achieve&p=148726"},"modified":"2026-04-13T15:46:27","modified_gmt":"2026-04-13T06:46:27","slug":"camel-research-team-has-been-successively-selected-for-2023-samsung-future-technology-development-program","status":"publish","type":"research-achieve","link":"http:\/\/ee.presscat.kr\/en\/research-achieve\/camel-research-team-has-been-successively-selected-for-2023-samsung-future-technology-development-program\/","title":{"rendered":"CAMEL research team has been successively selected for 2023 Samsung Future Technology Development Program"},"content":{"rendered":"

CAMEL research team has been successively selected for 2023 Samsung Future Technology Development Program<\/span><\/strong><\/span><\/p>\n

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The CAMEL research team from our department, led by Professor Myoungsoo Jung, has been chosen to participate in the Samsung Future Technology Development Program.<\/span><\/p>\n

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This recognition comes with support for their study titled, “Software-Hardware Co-Design for Dynamic Acceleration in Sparsity-aware Hyperscale AI.”<\/span><\/p>\n

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Large AI models, such as mixture of experts (MoE), autoencoders, and multimodal learning, grouped under the umbrella of Hyperscale AI, have gained traction due to the success of expansive model-driven applications, including ChatGPT.<\/span><\/p>\n

Based on the insight that computational traits of these models often shift during training, the research team has suggested acceleration strategies.<\/span><\/p>\n

These encompass software technologies, unique algorithms, and hardware accelerator layouts.<\/span><\/p>\n

A key discovery by the team was the inability of existing training systems to account for variations in data sparsity and computational dynamics between model layers. This oversight obstructs adaptive acceleration.\u00a0<\/span><\/p>\n

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To address this, the CAMEL team introduced a dynamic acceleration method that can detect shifts in computational traits and adapt computation techniques in real-time.<\/span><\/p>\n

The findings from this research could benefit not only Hyperscale AI but also the larger domain of deep learning and the burgeoning services sector.<\/span><\/p>\n

The team’s goals include producing tangible hardware models and offering open-source software platforms.<\/span><\/p>\n

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Samsung Electronics, since 2013, has initiated the ‘Future Technology Development Program’, investing KRW 1.5 trillion to stimulate technological innovation pivotal for future societal progress. <\/span><\/p>\n

For a decade, they have backed initiatives in foundational science, innovative materials, and ICT, particularly favoring ventures that are high-risk but offer significant returns.<\/span><\/p>\n

The CAMEL team has been collaborating with Samsung since 2021 on a project focusing on accelerating Graph Neural Networks (GNNs). We extend our hearty congratulations to them as they embark on this fresh exploration into the realm of Hyperscale AI.<\/span><\/p>\n

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