SK hynix Unveils Processing-In-Memory (PIM) for AI Bottlenecks
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SK hynix has presented a vision to solve the artificial intelligence (AI) data bottleneck by fronting processing-in-memory (PIM) technology, which allows memory semiconductors to perform a certain level of simple calculations. Im Eui-chul, vice president in charge of Solution AT at SK hynix, took the stage as a speaker at the AI Infra Summit held at the Santa Clara Convention Center in California, the United States, on Sept. 16 (local time), stating that the company will overcome the limitations of AI infrastructure centered on graphics processing units (GPUs) and high bandwidth memory (HBM) with PIM. Unlike the existing structure where data is moved from memory to AI accelerators such as graphics processing units (GPUs) for calculation and then transmitted back to memory, PIM is a method in which simple calculations are directly processed by a processing unit inside the memory. By reducing data movement between the memory and the processor, it can increase AI processing speed and power efficiency. Samsung Electronics also announced PIM targeting on-device AI at the semiconductor academic conference Hot Chips held last month. Vice President Im mentioned that the AI industry currently mainly uses SRAM when ultra-high-speed inference is required, pointing out, "SRAM-based systems provide high bandwidth, but there are clear limitations in terms of capacity and cost." He further...
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