To The Moon

When we looked at the world of AI, there is a desperate search for an alternative search for an alternative to $NVIDIA Corp(NVDA)$ CPUs, and $Advanced Micro Devices(AMD)$ is stepping up to the plate.

AMD detailed its updated GPU roadmap, with new hardware coming in 2024, 2025 and 2026. AMD previously released GPUs on a roughly 1.5- to two-year cycle, but overwhelming demand for AI hardware is weighing on the company.

For the first time, AMD announced the MI400 GPUs, which the company will release in 2026. It is positioned as the Nvidia GPU killer for 2026. AMD’s plans for 2024 include the MI325X GPU, followed by the 3-nanometer MI350 next year in 2025, with both based on HBM3E memory.

AMD Roadmap Clearer Now

AMD’s GPU sales are growing nicely, but the company has not provided a clear roadmap until June 2024. Analysts were uncomfortable about a lack of information on AMD’s GPU plans in 2025 and 2026, considering Nvidia outlined annual GPU plans in 2025 and 2026 last year.

This is despite AMD’s CEO mentioning that the company’s roadmap was driven by customer feedback.

AMD’s approach aligns with the fast-changing computing requirements of AI workloads. Training AI models drove initial GPU sales, and there is a wider focus on answering user queries against LLMs.

Data Center Segment Revenue Still Far From Nvidia

Even though AMD’s CEO has mentioned in the earnings calls that AMD’s MI300 sales are exploding and totaled $1 billion in less than two quarters. AMD is expecting data center GPU revenue to exceed $4 billion in 2024, up from the $3.5 billion we guided in January 2024.

AMD’s data center revenue in the most recent quarter was $2.3 billion, compared to Nvidia’s $22.6 billion. AMD is still trailing Nvidia in market share but is seeing wider customer adoption.

Microsoft helped AMD develop MI300X GPUs and announced last month that it was offering the accelerator in its ND MI300X v5 VM on Azure. A block of eight AMD MI300X GPUs includes 1.5 TB of HBM and 5.3 terabits per second of HBM bandwidth. Microsoft offers a wide range of GPUs and plans to bring Nvidia’s Blackwell GPUs to Azure.

The Upcoming GPUs

AMD’s 2024 GPU includes the MI325X accelerator, which will be out by the end of this year. It will be an upgrade to the current MI300 series and will be available by the end of the year.

The 325X will include 288GB of HBM3E memory and six terabytes per second of memory bandwidth. Nvidia has put HBM3E memory in its H200 GPU. The MI325X has backward compatibility, suggesting it is only a memory upgrade.

AMD’s 2025 GPU is the MI350 series, which the company claimed will deliver a 35x boost in inferencing compared to the MI300 series GPUs. Beyond the claim, AMD is trying to highlight the architectural improvements for inferencing, which is becoming more important than training.

The MI350 will be made using the 3-nanometer process.

Inferencing allows low-power AI processing to answer questions on trained models, and the claim is an indirect way of AMD boasting improvements for lower-precision FP4 or FP6 data types. Nvidia has put the FP4 and FP6 data types in its Blackwell GPU, which was announced in March.

AMD’s CPU Improvements

AMD said its 5th Gen AMD processors, code-named “Turin“ and based on the Zen 5 x86 architecture, will ship within the next six months. The chips, with up to 192 cores and 384 threads, will compete with Intel’s Granite Rapids CPUs.

The company also announced the Embedded+ chip design, which pairs its Ryzen CPU with the Versal AI chip. The chip will go into embedded products, such as robots, which need AI capabilities on the edge. Typically, AI chips such as FPGAs or ASICs cannot boot up devices on their own and rely on CPUs like AMD’s Ryzen for instructions and offload capabilities.

The Embedded+ chip architecture is a result of AMD uniting its CPU technology with Xilinx’s ASIC/FPGA designs.

ROCm IT

AMD said it continued to mature its software development tools, ROCm, to support the new GPUs. AMD has acknowledged that it has a lot of work to do on developer support for AI. There’s no coordination on software releases with support for tensor cores in the new GPUs, though the MI325 GPU backward compatibility suggests no environmental changes.

Nvidia coordinates the releases of its CUDA versions with the release of new GPUs.  Nvidia GPUs typically have newly architected tensor cores and GPU improvements, which involve new libraries that developers can use to fine-tune their applications for the new GPUs.

However, CUDA is proprietary, which means Nvidia locks customers into buying their software development tools, such as AI Enterprise, to take advantage of its latest GPUs.

AMD has been up 28% in the last 12 months versus Nvidia, which has gained 128%.

Semiconductor and AI-linked stocks, including Nvidia and AMD, faced a continued selloff despite strong quarterly results from Nvidia and $Broadcom(AVGO)$.

VanEck Semiconductor ETF SMH and iShares Semiconductor ETF SOXX risen over 2% in the past five days.

Summary

I would think that AMD would be winning on the end user computing devices chips side, considering that AI inference is picking up and AMD has cleared up their messy chip roadmap. We should be seeing more companies going to AMD for building their end user computing AI chips.

I am watching the AMD price action to prepare to load more of AMD shares.

Appreciate if you could share your thoughts in the comment section whether you think AMD would be having a potential long term upside considering the demand for end user computing chips.

@TigerStars @Daily_Discussion @Tiger_Earnings @TigerWire appreciate if you could feature this article so that fellow tiger would benefit from my investing and trading thoughts.

Disclaimer: The analysis and result presented does not recommend or suggest any investing in the said stock. This is purely for Analysis.