The 63rd edition of the TOP500 reveals that Frontier has once again claimed the top spot, despite no longer being the only exascale machine on the list. Additionally, a new system has found its way into the Top 10.

The Frontier system at Oak Ridge National Laboratory in Tennessee, USA remains the most powerful system on the list with an HPL score of 1.206 EFlop/s. The system has a total of 8,699,904 combined CPU and GPU cores, an HPE Cray EX architecture that combines 3rd Gen AMD EPYC CPUs optimized for HPC and AI with AMD Instinct MI250X accelerators, and it relies on Cray's Slingshot 11 network for data transfer. On top of that, this machine has an impressive power efficiency rating of 52.93 GFlops/Watt - putting Frontier at the No. 13 spot on the GREEN500.

AMD recently revealed its Instinct MI300X GPU at their Data Center and AI Technology Premiere event on Tuesday (June 15). The keynote presentation did not provide any details about the new accelerator model's power consumption, but that did not stop one tipster - Hoang Anh Phu - from obtaining this information from Team Red's post-event footnotes. A comparative observation was made: "MI300X (192 GB HBM3, OAM Module) TBP is 750 W, compared to last gen, MI250X TBP is only 500-560 W." A leaked Giga Computing roadmap from last month anticipated server-grade GPUs hitting the 700 W mark.

NVIDIA's Hopper H100 took the crown - with its demand for a maximum of 700 W - as the most power-hungry data center enterprise GPU until now. The MI300X's OCP Accelerator Module-based design now surpasses Team Green's flagship with a slightly greater rating. AMD's new "leadership generative AI accelerator" sports 304 CDNA 3 compute units, which is a clear upgrade over the MI250X's 220 (CDNA 2) CUs. Engineers have also introduced new 24G B HBM3 stacks, so the MI300X can be specced with 192 GB of memory (as a maximum), the MI250X is limited to a 128 GB memory capacity with its slower HBM2E stacks. We hope to see sample units producing benchmark results very soon, with the MI300X pitted against H100.

Increasing its HPL score from 1.02 Eflop/s in November 2022 to an impressive 1.194 Eflop/s on this list, Frontier was able to improve upon its score after a stagnation between June 2022 and November 2022. Considering exascale was only a goal to aspire to just a few years ago, a roughly 17% increase here is an enormous success. Additionally, Frontier earned a score of 9.95 Eflop/s on the HLP-MxP benchmark, which measures performance for mixed-precision calculation. This is also an increase over the 7.94 EFlop/s that the system achieved on the previous list and nearly 10 times more powerful than the machine's HPL score. Frontier is based on the HPE Cray EX235a architecture and utilizes AMD EPYC 64C 2 GHz processors. It also has 8,699,904 cores and an incredible energy efficiency rating of 52.59 Gflops/watt. It also relies on gigabit ethernet for data transfer.

According to TrendForce's latest survey of the server market, many cloud service providers (CSPs) have begun large-scale investments in the kinds of equipment that support artificial intelligence (AI) technologies. This development is in response to the emergence of new applications such as self-driving cars, artificial intelligence of things (AIoT), and edge computing since 2018. TrendForce estimates that in 2022, AI servers that are equipped with general-purpose GPUs (GPGPUs) accounted for almost 1% of annual global server shipments. Moving into 2023, shipments of AI servers are projected to grow by 8% YoY thanks to ChatBot and similar applications generating demand across AI-related fields. Furthermore, shipments of AI servers are forecasted to increase at a CAGR of 10.8% from 2022 to 2026.

During its CES 2023 keynote, AMD announced its latest Instinct MI300 APU, a first of its kind in the data center world. Combining the CPU, GPU, and memory elements into a single package eliminates latency imposed by long travel distances of data from CPU to memory and from CPU to GPU throughout the PCIe connector. In addition to solving some latency issues, less power is needed to move the data and provide greater efficiency. The Instinct MI300 features 24 Zen4 cores with simultaneous multi-threading enabled, CDNA3 GPU IP, and 128 GB of HBM3 memory on a single package. The memory bus is 8192-bit wide, providing unified memory access for CPU and GPU cores. CLX 3.0 is also supported, making cache-coherent interconnecting a reality.

The Instinct MI300 APU package is an engineering marvel of its own, with advanced chiplet techniques used. AMD managed to do 3D stacking and has nine 5 nm logic chiplets that are 3D stacked on top of four 6 nm chiplets with HBM surrounding it. All of this makes the transistor count go up to 146 billion, representing the sheer complexity of a such design. For performance figures, AMD provided a comparison to Instinct MI250X GPU. In raw AI performance, the MI300 features an 8x improvement over MI250X, while the performance-per-watt is "reduced" to a 5x increase. While we do not know what benchmark applications were used, there is a probability that some standard benchmarks like MLPerf were used. For availability, AMD targets the end of 2023, when the "El Capitan" exascale supercomputer will arrive using these Instinct MI300 APU accelerators. Pricing is unknown and will be unveiled to enterprise customers first around launch.

When AMD announced that the company would deliver the world's fastest supercomputer, Frontier, the company also took a massive task to provide a machine capable of producing one ExaFLOP of total sustained ability to perform computing tasks. While the system is finally up and running, making a machine of that size run properly is challenging. In the world of High-Performance Computing, getting the hardware is only a portion of running the HPC center. In an interview with InsideHPC, Justin Whitt, program director for the Oak Ridge Leadership Computing Facility (OLCF), provided insight into what it is like to run the world's fastest supercomputer and what kinds of issues it is facing.

The Frontier system is powered by AMD EPYC 7A53s "Trento" 64-core 2.0 GHz CPUs and Instinct MI250X GPUs. Interconnecting everything is the HPE (Cray) Slingshot 64-port switch, which is responsible for sending data in and out of compute blades. The recent interview points out a rather interesting finding: exactly AMD Instinct MI250X GPUs and Slingshot interconnect cause hardware troubles for the Frontier. "It's mostly issues of scale coupled with the breadth of applications, so the issues we're encountering mostly relate to running very, very large jobs using the entire system … and getting all the hardware to work in concert to do that," says Justin Whitt. In addition to the limits of scale "The issues span lots of different categories, the GPUs are just one. A lot of challenges are focused around those, but that's not the majority of the challenges that we're seeing," he said. "It's a pretty good spread among common culprits of parts failures that have been a big part of it. I don't think that at this point that we have a lot of concern over the AMD products. We're dealing with a lot of the early-life kind of things we've seen with other machines that we've deployed, so it's nothing too out of the ordinary."

AMD in its HotChips 22 presentation released a block-diagram of its biggest AI-HPC processor, the Instinct MI250X. Based on the CDNA2 compute architecture, at the heart of the MI250X is the "Aldebaran" MCM (multi-chip module). This MCM contains two logic dies (GPU dies), and eight HBM2E stacks, four per GPU die. The two GPU dies are connected by a 400 GB/s Infinity Fabric link. They each have up to 500 GB/s of external Infinity Fabric bandwidth for inter-socket communications; and PCI-Express 4.0 x16 as the host system bus for AIC form-factors. The two GPU dies together make up 58 billion transistors, and are fabricated on the TSMC N6 (6 nm) node.

The component hierarchy of each GPU die sees eight Shader Engines share a last-level L2 cache. The eight Shader Engines total 112 Compute Units, or 14 CU per engine. The CDNA2 compute unit contains 64 stream processors making up the Shader Core, and four Matrix Core Units. These are specialized hardware for matrix/tensor math operations. There are hence 7,168 stream processors per GPU die, and 14,336 per package. AMD claims a 100% increase in double-precision compute performance over CDNA (MI100). AMD attributes this to increases in frequencies, efficient data paths, extensive operand reuse and forwarding; and power-optimization enabling those higher clocks. The MI200 is already powering the Frontier supercomputer, and is working for more design wins in the HPC space. The company also dropped a major hint that the MI300, based on CDNA3, will be an APU. It will incorporate GPU dies, core-logic, and CPU CCDs onto a single package, in what is a rival solution to NVIDIA Grace Hopper Superchip.

AMD today announced the new AMD Instinct MI200 series accelerators, the first exascale-class GPU accelerators. AMD Instinct MI200 series accelerators includes the world's fastest high performance computing (HPC) and artificial intelligence (AI) accelerator,1 the AMD Instinct MI250X.

Built on AMD CDNA 2 architecture, AMD Instinct MI200 series accelerators deliver leading application performance for a broad set of HPC workloads. The AMD Instinct MI250X accelerator provides up to 4.9X better performance than competitive accelerators for double precision (FP64) HPC applications and surpasses 380 teraflops of peak theoretical half-precision (FP16) for AI workloads to enable disruptive approaches in further accelerating data-driven research.

AMD today announced the debut of its 6 nm CDNA2 (Compute-DNA) architecture in the form of the MI200 family. The new, dual-GPU chiplet accelerator aims to lead AMD into a new era of High Performance Computing (HPC) applications, the high margin territory it needs to compete in for continued, sustainable growth. To that end, AMD has further improved on a matured, compute-oriented architecture born with Graphics Core Next (GCN) - and managed to improve performance while reducing total die size compared to its MI100 family.