Recently, the JEDEC Solid State Technology Association officially released the highly anticipated HBM4 standard, which is a major evolution of the HBM3 standard. It focuses on further improving the speed of data processing, while taking into account important characteristics such as high bandwidth, low power consumption, and high capacity. In today's era of explosive data volume, from generative AI to high-performance computing, from high-end graphics cards to servers, the need for efficient processing of massive amounts of data and complex calculations is becoming more and more urgent, and the timely launch of the HBM4 standard undoubtedly provides a powerful "fuel" for these fields.
From a technical perspective, the advantages of the HBM4 standard are significant. With transfer speeds of up to 8Gb/s and a total bandwidth of 2TB/s through a 2048-bit interface, this is a significant jump over HBM3, which means that data is transferred faster between memory and processor, greatly reducing latency and significantly improving overall system performance. The number of independent channels has been doubled from 16 to 32 in HBM3, and each channel is equipped with 2 pseudo-channels, providing designers with more design flexibility and more efficient access to stored data to meet the diverse needs of different application scenarios.
In terms of power consumption management, HBM4 supports a variety of specific voltage levels, such as VDDQ (0.7V, 0.75V, 0.8V or 0.9V) and VDDC (1.0V or 1.05V), which enables the chip to accurately adjust the voltage according to the actual needs during operation, thereby reducing power consumption and improving energy efficiency, which is of great significance for modern data centers and various electronic products that pursue green energy saving.
Compatibility is also a highlight of HBM4. Its interface definition ensures backward compatibility with existing HBM3 controllers, which means that when upgrading to HBM4, enterprises do not need to replace existing equipment and controllers on a large scale, greatly reducing the upgrade cost and technical threshold, and can realize the seamless connection between new and old products, which provides convenience for market promotion and application popularization.
Figure: HBM4 Standard Release: Giving New Impetus to High-Performance Computing and AI
In addition, the Directed Refresh Management (DRFM) technology introduced in HBM4 effectively mitigates the hammer effect and improves the reliability, availability, and maintainability (RAS) of memory. In terms of capacity configuration, it supports a variety of DRAM stack configurations, from 4-high to 16-high, and the chip density is available in 24Gb or 32Gb, and can achieve a cube density of up to 64GB, which fully meets the storage capacity needs of different applications.
The release of the HBM4 standard has been highly recognized and actively supported by many industry giants. Barry Wagner, director of technical marketing at NVIDIA, noted that the rapid development of high-performance computing platforms is inseparable from innovations in memory, bandwidth, and capacity, and that HBM4 will push AI and other accelerated applications to a new level of high-performance computing. AMD is proud to be a part of the development of the standard for the performance, efficiency, and scalability enhancements of HBM4 that will power the next generation of AI, high-performance computing, and graphics workloads, according to AMD senior vice president Joe Macri.
Executives from Cadence, Google Cloud Silicon, Meta, Micron, Samsung, SK hynix, Synopsys, and others have also expressed praise for the HBM4 standard. They agreed that the emergence of the HBM4 standard accurately meets the urgent needs of high-bandwidth and large-capacity memory in the fields of artificial intelligence and high-performance computing, and will strongly promote the further development of related technologies.
It is foreseeable that with the gradual application of the HBM4 standard, major semiconductor manufacturers will launch a series of high-performance storage products based on this standard. In the field of artificial intelligence, the speed of training and inference will be greatly improved, enabling AI models to handle more complex tasks and promoting the in-depth application of AI technology in multiple industries such as healthcare, finance, and autonomous driving. In terms of high-performance computing, the computing power of supercomputers will be taken to the next level, bringing more accurate simulations and predictions to scientific research, weather forecasting, and other fields.
