What ‘GDDR7’ is and why it promises performance gains for AI

The rise of GDDR7 memory in AI inference: GDDR7, the latest graphics memory solution, is set to revolutionize AI inference with its exceptional bandwidth and low latency capabilities, making it ideal for AI-powered edge and endpoint devices.

• GDDR7 offers a performance roadmap of up to 48 Gigatransfers per second (GT/s) and memory throughput of 192 GB/s per device, significantly outperforming previous generations.
• This new memory standard is expected to be utilized in the next generation of GPUs and accelerators for AI inference workloads.

AI training vs. inference requirements: While AI training demands high memory bandwidth and capacity, inference prioritizes throughput speed and low latency, especially for real-time applications.

• AI training models are growing in size and complexity at a rate of 10X per year, necessitating enormous amounts of data and specialized silicon solutions.
• Inference engines need to process various media types, including text, images, speech, music, and video, often in real-time scenarios.

GDDR7’s bandwidth advantage: The new memory standard offers exceptional bandwidth capabilities, making it particularly suitable for demanding AI inference workloads.

• At a data rate of 32 GT/s and a 32-bit wide interface, a GDDR7 device can deliver 128 GB/s of memory bandwidth.
• This performance is more than double that of memory solutions like LPDDR5T, positioning GDDR7 as a top choice for AI applications.

Technical advancements in GDDR7: The latest iteration of GDDR memory introduces several key improvements over its predecessor, GDDR6.

• GDDR7 employs three-bit pulse amplitude modulating (PAM3) encoding, allowing for a 50% increase in data transmission compared to GDDR6 at the same clock speed.
• The JEDEC specification for GDDR7 allows for future expansion of data rates up to 48 GT/s, with initial devices expected to run at around 32 GT/s.
• Enhanced reliability features include on-die ECC with real-time reporting, data poison, error check and scrub, and command address parity with command blocking (CAPARBLK).
• GDDR7 uses four 10-bit channels (8 bits data, 2 bits error reporting), compared to GDDR6’s two 16-bit channels.

Rambus GDDR7 Controller IP: This controller is designed to leverage the full potential of GDDR7 memory in high-performance applications.

• The controller supports GDDR7 performance of up to 40 GT/s and 160 GB/s of available bandwidth per memory device.
• It offers compatibility with all GDDR7 link features, including PAM3 and NRZ signaling, CRC with retry for reads and writes, data scramble, data poison, clamshell mode, and DQ logical remap.
• The controller accepts commands using AXI or a simple local interface and supports all low-power modes.

Implications for AI acceleration: The advent of GDDR7 memory is poised to significantly impact the development and deployment of AI inference solutions.

• As AI inference models grow in size and sophistication, the demand for more powerful AI accelerators and GPUs in edge servers and client PCs increases.
• GDDR7’s combination of high bandwidth and low latency makes it an excellent choice for keeping these inference processors and accelerators supplied with data efficiently.
• This advancement in memory technology is likely to enable more complex and responsive AI applications at the edge, potentially opening up new use cases and improving existing ones.