10,000-Word In-Depth Analysis of AMD's CDNA 4 Architecture
AMD's CDNA 4 GPU architecture boosts AI performance with enhanced matrix math, HBM3E memory & chiplet design for machine learning workloads.
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CDNA 4 is AMD's latest compute-focused GPU architecture, representing a moderate update over CDNA 3. CDNA 4 is primarily dedicated to improving AMD's matrix multiplication performance at low-precision data types. These operations are crucial for machine learning workloads, as machine learning workloads can typically maintain acceptable accuracy at extremely low precision types. Meanwhile, CDNA 4 strives to maintain AMD's leadership in vector operations for broader applications.
To this end, CDNA 4 largely adopts the same system-level architecture as CDNA 3. It employs a large-scale chiplet setup, similar to AMD's successful application of chiplets in its CPU products. The accelerator compute chiplets (XCD) contain CDNA compute units, functioning similarly to the core complex dies (CCD) on AMD's CPU products. Eight XCDs sit atop four base chiplets that implement 256 MB of memory-side cache. AMD's Infinity Fabric technology provides coherent memory access throughout the system and can span multiple chiplets.
Compared to the CDNA 3-based MI300X, the CDNA 4-powered MI355X slightly reduces the number of CUs per XCD and disables more CUs to maintain yield. The resulting GPU width is slightly smaller, but higher clock speeds compensate for most of the gap. Compared to Nvidia's B200, both the MI355X and MI300 are larger GPUs with more fundamental building blocks. Nvidia's B200 does employ a multi-chiplet strategy, breaking from the long-standing tradition of using monolithic designs. However, AMD's chiplet setup is more aggressive and attempts to replicate its scaling success from CPU designs with large compute GPUs.