Google Develops Hardware and Software to Tackle AI Memory Bottleneck, Recycles DDR4
Google's senior director of supply chain infrastructure, Nikhil Cherian, revealed the company is developing both software and hardware solutions to address memory constraints in AI servers. The approach includes salvaging DDR4 modules from retired servers, designing custom adapters to connect older memory to next-generation servers, and importing retired servers for DDR4 removal. Cherian noted that AI has shifted from compute-constrained to memory-constrained, with high-performance memory consuming about 75% of an AI server's bill of materials. Goldman Sachs expects third-quarter PC DRAM prices to rise 18% to 23% and server DRAM 13% to 18%. Trendforce data shows spot prices for DDR4 8GB and DDR5 8GB reached $142 and $133 in August. Google's two new TPU ASICs this year feature memory-optimized designs, potentially reducing memory requirements by a factor of six, with the TPU8i chip packing 288GB of HBM3e memory.








