The Importance of Memory Architecture for AI SoCs
The rapid advance of artificial intelligence (AI) is impacting everything from how we drive to how we make business decisions and shop. Enabled by the massive and growing volume of big data, AI is also causing compute demand to balloon. In fact, the most recent generative AI models require a 10 to 100-fold increase in computing power to train models compared to the previous generation, which is, in turn, doubling overall demand about every six months.
As you might expect, this has led to a computing transformation that has, in part, been made possible due to new types of memory architectures. These advanced graphics processing unit (GPU) architectures are opening up dramatic new possibilities for designers. The key is choosing the right memory architecture for the task at hand and the right memory to deploy for that architecture.
To be sure, there is an array of more efficient emerging memories out there for specific tasks. They include compute-in-memory SRAM (CIM), STT-MRAM, SOT-MRAM, ReRAM, CB-RAM, and PCM. While each has different properties, as a collective unit they serve to enhance compute power while raising energy efficiency and reducing cost. These are key factors that must be considered to develop economical and sustainable AI SoCs.
Many considerations affect a designer’s choice of architecture according to the priorities of any given application. These include throughput, modularity and scalability, thermal management, speed, reliability, processing compatibility with CMOS, power delivery, cost, and the need for analog behavior that mimics human neurons.
Let’s examine the features of the assorted emerging memories currently at a designer’s disposal.
Related Semiconductor IP
- High Speed Ethernet Quad 10G to 100G PCS
- High Speed Ethernet Gen-2 Quad 100G PCS IP
- High Speed Ethernet 4/2/1-Lane 100G PCS
- High Speed Ethernet 2/4/8-Lane 200G/400G PCS
- High Speed Ether 2/4/8-Lane 200G/400G/800G PCS
Related Blogs
- The Evolving Role of Layout-Versus-Schematic (LVS) Checking for Modern SoCs
- The Importance of Ecosystem Cooperation for Interoperability
- Exploring the Security Framework of RISC-V Architecture in Modern SoCs
- Innovative Memory Architectures for AI
Latest Blogs
- Why Choose Hard IP for Embedded FPGA in Aerospace and Defense Applications
- Migrating the CPU IP Development from MIPS to RISC-V Instruction Set Architecture
- Quintauris: Accelerating RISC-V Innovation for next-gen Hardware
- Say Goodbye to Limits and Hello to Freedom of Scalability in the MIPS P8700
- Why is Hard IP a Better Solution for Embedded FPGA (eFPGA) Technology?