NVIDIA's Compute Unified Device Architecture (CUDA) has long been the de facto standard programming interface for developing GPU-accelerated software. Over the years, NVIDIA has built an entire ecosystem around CUDA, cementing its position as the leading GPU computing and AI manufacturer. However, rivals AMD and Intel have been trying to make inroads with their own open API offerings—ROCm from AMD and oneAPI from Intel. The idea was that developers could more easily run existing CUDA code on non-NVIDIA GPUs by providing open access through translation layers. Developers had created projects like ZLUDA to translate CUDA to ROCm, and Intel's CUDA to SYCL aimed to do the same for oneAPI. However, with the release of CUDA 11.5, NVIDIA appears to have cracked down on these translation efforts by modifying its terms of use, according to developer Longhorn on X.

"You may not reverse engineer, decompile or disassemble any portion of the output generated using Software elements for the purpose of translating such output artifacts to target a non-NVIDIA platform," says the CUDA 11.5 terms of service document. The changes don't seem to be technical in nature but rather licensing restrictions. The impact remains to be seen, depending on how much code still requires translation versus running natively on each vendor's API. While CUDA gave NVIDIA a unique selling point, its supremacy has diminished as more libraries work across hardware. Still, the move could slow the adoption of AMD and Intel offerings by making it harder for developers to port existing CUDA applications. As GPU-accelerated computing grows in fields like AI, the battle for developer mindshare between NVIDIA, AMD, and Intel is heating up.

The latest version of AMD's open-source GPU compute stack, ROCm, is due for launch soon according to a Phoronix article—chief author, Michael Larabel, has been poring over Team Red's public GitHub repositories over the past couple of days. AMD ROCm version 6.0 was released last December—bringing official support for the AMD Instinct MI300A/MI300X, alongside PyTorch improvements, expanded AI libraries, and many other upgrades and optimizations. The v6.0 milestone placed Team Red in a more competitive position next to NVIDIA's very mature CUDA software layer. A mid-February 2024 update added support for Radeon PRO W7800 and RX 7900 GRE GPUs, as well as ONNX Runtime.

Larabel believes that "ROCm 6.1" is in for an imminent release, given his tracking of increased activity on publicly visible developer platforms: "For MIPOpen 3.1 with ROCm 6.1 there's been many additions including new solvers, an AI-based parameter prediction model for the conv_hip_igemm_group_fwd_xdlops solver, numerous fixes, and other updates. AMD MIGraphX will see an important update with ROCm 6.1. For the next ROCm release, MIGraphX 2.9 brings FP8 support, support for more operators, documentation examples for Whisper / Llama-2 / Stable Diffusion 2.1, new ONNX examples, BLAS auto-tuning for GEMMs, and initial code for MIGraphX running on Microsoft Windows." The change-logs/documentation updates also point to several HIPIFY for ROCm 6.1 improvements—including the addition of CUDA 12.3.2 support.

Building on our previously announced support of the AMD Radeon RX 7900 XT, XTX and Radeon PRO W7900 GPUs with AMD ROCm 5.7 and PyTorch, we are now expanding our client-based ML Development offering, both from the hardware and software side with AMD ROCm 6.0. Firstly, AI researchers and ML engineers can now also develop on Radeon PRO W7800 and on Radeon RX 7900 GRE GPUs. With support for such a broad product portfolio, AMD is helping the AI community to get access to desktop graphics cards at even more price points and at different performance levels.

Furthermore, we are complementing our solution stack with support for ONNX Runtime. ONNX, short for Open Neural Network Exchange, is an intermediary Machine Learning framework used to convert AI models between different ML frameworks. As a result, users can now perform inference on a wider range of source data on local AMD hardware. This also adds INT8 via MIGraphX—AMD's own graph inference engine—to the available data types (including FP32 and FP16). With AMD ROCm 6.0, we are continuing our support for the PyTorch framework bringing mixed precision with FP32/FP16 to Machine Learning training workflows.

AMD has quietly funded an effort over the past two years to enable binary compatibility for NVIDIA CUDA applications on their ROCm stack. This allows CUDA software to run on AMD Radeon GPUs without adapting the source code. The project responsible is ZLUDA, which was initially developed to provide CUDA support on Intel graphics. The developer behind ZLUDA, Andrzej Janik, was contracted by AMD in 2022 to adapt his project for use on Radeon GPUs with HIP/ROCm. He spent two years bringing functional CUDA support to AMD's platform, allowing many real-world CUDA workloads to run without modification. AMD decided not to productize this effort for unknown reasons but did open-source it once funding ended per their agreement. Over at Phoronix, there were several benchmarks testing AMD's ZLUDA implementation over a wide variety of benchmarks.

Benchmarks found that proprietary CUDA renderers and software worked on Radeon GPUs out-of-the-box with the drop-in ZLUDA library replacements. CUDA-optimized Blender 4.0 rendering now runs faster on AMD Radeon GPUs than the native ROCm/HIP port, reducing render times by around 10-20%, depending on the scene. The implementation is surprisingly robust, considering it was a single-developer project. However, there are some limitations—OptiX and PTX assembly codes still need to be fully supported. Overall, though, testing showed very promising results. Over the generic OpenCL runtimes in Geekbench, CUDA-optimized binaries produce up to 75% better results. With the ZLUDA libraries handling API translation, unmodified CUDA binaries can now run directly on top of ROCm and Radeon GPUs. Strangely, the ZLUDA port targets AMD ROCm 5.7, not the newest 6.x versions. Only time will tell if AMD continues investing in this approach to simplify porting of CUDA software. However, the open-sourced project now enables anyone to contribute and help improve compatibility. For a complete review, check out Phoronix tests.

References to GFX1150 & GFX1151 targets have been spotted again—this time in a ROCm Github repository—by renowned hardware sleuth; Kepler_L2. These references were first spotted last summer, in an AMDGPU LLVM backend/compiler (reported by Phoronix)—industry experts immediately linked these target codes to next generation "Strix" APU families. The latest leak provides confirmation that the GFX1150 ID is tied to "Strix Point 1," while GFX1151 is an internal IP for "Strix Point Halo," or simply "Strix Halo." The freshly published ROCm Github's commit is titled: "Strix Halo Support and Strix support in staging," which corroborates previous rumors regarding Team Red's engineers being deep into development of Zen 5 (and RDNA 3.5)-based accelerated processing units.

AMD has published several processor product roadmaps with references to "Strix Point" next-gen APUs, with a targeted 2024 launch window. Their December 2023 "Advancing AI Event" confirmed that the "Strix Point" mobile family will sport "XDNA 2" NPUs—previous generation "Phoenix" and recently released "Hawk Point" processors are on the first iteration of XDNA (a spatial dataflow NPU architecture). It is speculated that a typical "Strix Point" laptop processor will pack 12 Zen 5 CPU cores and 16 RDNA 3.5 GPU cores. Team Red has kept quiet about "Strix Halo" (also known as "Sarlak") when conducting public-facing presentations—a loose 2025 launch window is being touted by the rumor mill. The most advanced examples could feature up to 16 Zen 5 CPU cores and 40 RDNA 3.5 GPU cores.

LaminiAI appears to be one of AMD's first customers to receive a bulk order of Instinct MI300X GPUs—late last week, Sharon Zhou (CEO and co-founder) posted about the "next batch of LaminiAI LLM Pods" up and running with Team Red's cutting-edge CDNA 3 series accelerators inside. Her short post on social media stated: "rocm-smi...like freshly baked bread, 8x MI300X is online—if you're building on open LLMs and you're blocked on compute, lmk. Everyone should have access to this wizard technology called LLMs."

An attached screenshot of a ROCm System Management Interface (ROCm SMI) session showcases an individual Pod configuration sporting eight Instinct MI300X GPUs. According to official blog entries, LaminiAI has utilized bog-standard MI300 accelerators since 2023, so it is not surprising to see their partnership continue to grow with AMD. Industry predictions have the Instinct MI300X and MI300A models placed as great alternatives to NVIDIA's dominant H100 "Hopper" series—AMD stock is climbing due to encouraging financial analyst estimations.

Generative AI (GenAI) is the decade's most promising accelerator for innovation with 78% of IT decision makers reporting they're largely excited for the potential GenAI can have on their organizations.¹ Most see GenAI as a means to provide productivity gains, streamline processes and achieve cost savings. Harnessing this technology is critical to ensure organizations can compete in this new digital era.

Dell Technologies and AMD are coming together to unveil an expansion to the Dell Generative AI Solutions portfolio, continuing the work of accelerating advanced workloads and offering businesses more choice to continue their unique GenAI journeys. This new technology highlights a pivotal role played by open ecosystems and silicon diversity in empowering customers with simple, trusted and tailored solutions to bring AI to their data.

Today at the "Advancing AI" event, AMD was joined by industry leaders including Microsoft, Meta, Oracle, Dell Technologies, HPE, Lenovo, Supermicro, Arista, Broadcom and Cisco to showcase how these companies are working with AMD to deliver advanced AI solutions spanning from cloud to enterprise and PCs. AMD launched multiple new products at the event, including the AMD Instinct MI300 Series data center AI accelerators, ROCm 6 open software stack with significant optimizations and new features supporting Large Language Models (LLMs) and Ryzen 8040 Series processors with Ryzen AI.

"AI is the future of computing and AMD is uniquely positioned to power the end-to-end infrastructure that will define this AI era, from massive cloud installations to enterprise clusters and AI-enabled intelligent embedded devices and PCs," said AMD Chair and CEO Dr. Lisa Su. "We are seeing very strong demand for our new Instinct MI300 GPUs, which are the highest-performance accelerators in the world for generative AI. We are also building significant momentum for our data center AI solutions with the largest cloud companies, the industry's top server providers, and the most innovative AI startups ꟷ who we are working closely with to rapidly bring Instinct MI300 solutions to market that will dramatically accelerate the pace of innovation across the entire AI ecosystem."

Today, AMD announced the availability of the AMD Instinct MI300X accelerators - with industry leading memory bandwidth for generative AI and leadership performance for large language model (LLM) training and inferencing - as well as the AMD Instinct MI300A accelerated processing unit (APU) - combining the latest AMD CDNA 3 architecture and "Zen 4" CPUs to deliver breakthrough performance for HPC and AI workloads.

"AMD Instinct MI300 Series accelerators are designed with our most advanced technologies, delivering leadership performance, and will be in large scale cloud and enterprise deployments," said Victor Peng, president, AMD. "By leveraging our leadership hardware, software and open ecosystem approach, cloud providers, OEMs and ODMs are bringing to market technologies that empower enterprises to adopt and deploy AI-powered solutions."

AMD is working hard on delivering next-generation products, and today, its Linux team has submitted a few interesting patches that made a subtle appearance through recent GitHub patches for GFX12 targets, as reported by Phoronix. These patches have introduced two new discrete GPUs into the LLVM compiler for Linux, fueling speculation that these will be the first iterations of the RDNA4 graphics architecture, potentially being a part of the Radeon RX 8000 series of desktop graphics cards. The naming scheme for these new targets, GFX1200 and GFX1201, suggests a continuation of AMD's logical progression through graphics architectures, considering the company's history of associating RDNA1 with GFX10 and following suit with subsequent generations, like RDNA2 was GFX10.2 and RDNA3 was GFX11.

The development of these new GPUs is still in the early stages, indicated by the lack of detailed information about the upcoming graphics ISA or its features within the patches. Currently, the new GFX12 targets are set to be treated akin to GFX11 as the patch notes that "For now they behave identically to GFX11," implying that AMD is keeping the specifics under wraps until closer to release. The patch that defines target names and ELF numbers for new GFX12 targets GFX1200 and GFX1201 is needed in order to enable timely support for AMD ROCm compute stack, the AMDVLK Vulkan driver, and the RadeonSI Gallium3D driver.

Today, AMD released the findings from a new survey of global IT leaders which found that 3 in 4 IT leaders are optimistic about the potential benefits of AI—from increased employee efficiency to automated cybersecurity solutions—and more than 2 in 3 are increasing investments in AI technologies. However, while AI presents clear opportunities for organizations to become more productive, efficient, and secure, IT leaders expressed uncertainty on their AI adoption timeliness due to their lack of implementation roadmaps and the overall readiness of their existing hardware and technology stack.

AMD commissioned the survey of 2,500 IT leaders across the United States, United Kingdom, Germany, France, and Japan to understand how AI technologies are re-shaping the workplace, how IT leaders are planning their AI technology and related Client hardware roadmaps, and what their biggest challenges are for adoption. Despite some hesitations around security and a perception that training the workforce would be burdensome, it became clear that organizations that have already implemented AI solutions are seeing a positive impact and organizations that delay risk being left behind. Of the organizations prioritizing AI deployments, 90% report already seeing increased workplace efficiency.

AMD today announced the Radeon PRO W7600 and W7500 graphics cards for the professional-visualization (pro-vis) market segment. These cards target the mid-range of the pro-vis segment, with segment price-band ranging between $350-950. The two are hence positioned below the W7800 and W7900 that the company launched in April. The W7600 and W7500 are based on the same RDNA3 graphics architecture as those two, and the client-segment RX 7000 series. AMD is pricing the the two new cards aggressively compared to NVIDIA. Both the W7500 and W7600 are based on the 6 nm "Navi 33" silicon.

The Radeon PRO W7600 leads today's launch, maxing out the silicon it is based on—you get 32 RDNA3 compute units, or 2,048 stream processors; 64 AI Accelerators, 32 Ray Accelerators; 128 TMUs, and 64 ROPs. The card comes with 8 GB of 18 Gbps GDDR6 memory across a 128-bit wide memory bus. The memory does not feature ECC. The card comes with a 130 W typical power draw, with a single 6-pin PCIe power connector. It uses a slick single-slot lateral-airflow cooling solution. AMD claims 20 TFLOPs peak FP32 performance.

AMD today announced revenue for the second quarter of 2023 of $5.4 billion, gross margin of 46%, operating loss of $20 million, net income of $27 million and diluted earnings per share of $0.02. On a non-GAAP basis, gross margin was 50%, operating income was $1.1 billion, net income was $948 million and diluted earnings per share was $0.58.

"We delivered strong results in the second quarter as 4th Gen EPYC and Ryzen 7000 processors ramped significantly," said AMD Chair and CEO Dr. Lisa Su. "Our AI engagements increased by more than seven times in the quarter as multiple customers initiated or expanded programs supporting future deployments of Instinct accelerators at scale. We made strong progress meeting key hardware and software milestones to address the growing customer pull for our data center AI solutions and are on-track to launch and ramp production of MI300 accelerators in the fourth quarter."

AMD's "Vega" graphics architecture powering graphics cards such as the Radeon VII, Radeon PRO VII, sees a discontinuation of maintenance with ROCm GPU programming software stack. The release notes of ROCm 5.6 states that the AMD Instinct MI50 accelerator, Radeon VII client graphics card, and Radeon PRO VII pro-vis graphics card, collectively referred to as "gfx906," will reach EOM (end of maintenance) starting Q3-2023, which aligns with the release of ROCm 5.7. Developer "EwoutH" on GitHub, who discovered this, remarks gfx906 is barely 5 years old, with the Radeon PRO VII and Instinct MI50 accelerator currently being sold in the market. The most recent AMD product powered by "Vega" has to be the "Cezanne" desktop processor, which uses an iGPU based on the architecture. This chip was released in Q2-2021.

Today, at the "Data Center and AI Technology Premiere," AMD announced the products, strategy and ecosystem partners that will shape the future of computing, highlighting the next phase of data center innovation. AMD was joined on stage with executives from Amazon Web Services (AWS), Citadel, Hugging Face, Meta, Microsoft Azure and PyTorch to showcase the technological partnerships with industry leaders to bring the next generation of high performance CPU and AI accelerator solutions to market.

"Today, we took another significant step forward in our data center strategy as we expanded our 4th Gen EPYC processor family with new leadership solutions for cloud and technical computing workloads and announced new public instances and internal deployments with the largest cloud providers," said AMD Chair and CEO Dr. Lisa Su. "AI is the defining technology shaping the next generation of computing and the largest strategic growth opportunity for AMD. We are laser focused on accelerating the deployment of AMD AI platforms at scale in the data center, led by the launch of our Instinct MI300 accelerators planned for later this year and the growing ecosystem of enterprise-ready AI software optimized for our hardware."

A bunch of unreleased AMD Radeon RX 7000 series graphics card have been spotted in ROCm 5.6 pull request, including the Radeon RX 7950 XTX, 7950 XT, 7800 XT, 7700 XT, 7600 XT, and 7500 XT. AMD has not yet launched its mainstream Radeon RX 7000 graphics cards, but according to the latest pull request, there are several unreleased graphics cards in for both high-end and mainstream segments. While the pull request has been removed from GitHub, it has been saved on Reddit. So far, it appears that AMD's RDNA 3 Radeon 7000 series lineup will be based on just three GPUs, Navi 33, Navi 32, and the Navi 31.

According to the list, we can expect a high-end refresh with Radeon RX 7950 XTX/XT version, also based on Navi 31 GPU. The list also shows that the Radeon RX 7800 series will be the only one based on the Navi 32 GPU, at least for now, while the Navi 33 GPU should cover the entire mainstream lineup, including the Radeon RX 7700 series, Radeon RX 7600 series, and the Radeon RX 7500 series. The list only includes XT versions, while non-XT should show up later, as it was the case with the Radeon RX 6000 series graphics cards. AMD's President and CEO, Dr. Lisa Su, already confirmed during Q1 2023 earnings call that mainstream Radeon RX 7000 series GPUs based on RDNA 3 architecture will launch during this quarter, and earlier rumors suggest we might see them at Computex 2023.

As expected with AMD's activity on GitHub, ROCm 5.5 has now been officially released. It brings several big changes, including better RDNA 3 support. While officially focused on AMD's professional/workstation graphics cards, the ROCm 5.5 should also bring better support for Radeon RX 7000 series graphics cards on Linux.

Surprisingly, the release notes do not officially mention RDNA 3 improvements in its release notes, but those have been already tested and confirmed. The GPU support list is pretty short including AMD GFX9, RDNA, and CDNA GPUs, ranging from Radeon VII, Pro VII, W6800, V620, and Instinct lineup. The release notes do mention new HIP enhancements, enhanced stack size limit, raising it from 16k to 128k, new APIs, OpenMP enhancements, and more. You can check out the full release notes, downloads, and more details over at GitHub.

AMD has published an exciting development for its Radeon Open Compute Ecosystem (ROCm) users today. Now, ROCm is coming to the Windows operating system, and the company has extended ROCm support for consumer graphics cards instead of only supporting professional-grade GPUs. This development milestone is essential for making AMD's GPU family more competent with NVIDIA and its CUDA-accelerated GPUs. For those unaware, AMD ROCm is a software stack designed for GPU programming. Similarly to NVIDIA's CUDA, ROCm is designed for AMD GPUs and was historically limited to Linux-based OSes and GFX9, CDNA, and professional-grade RDNA GPUs.

However, according to documents obtained by Tom's Hardware (which are behind a login wall), AMD has brought support for ROCm to Radeon RX 6900 XT, Radeon RX 6600, and R9 Fury GPU. What is interesting is not the inclusion of RX 6900 XT and RX 6600 but the support for R9 Fury, an eight-year-old graphics card. Also, what is interesting is that out of these three GPUs, only R9 Fury has full ROCm support, the RX 6900 XT has HIP SDK support, and RX 6600 has only HIP runtime support. And to make matters even more complicated, the consumer-grade R9 Fury GPU has full ROCm support only on Linux and not Windows. The reason for this strange selection of support has yet to be discovered. However, it is a step in the right direction, as AMD has yet to enable more functionality on Windows and more consumer GPUs to compete with NVIDIA.

AMD today announced the appointment of five technical leaders to the role of AMD Corporate Fellow. These appointments recognize each leader's significant impact on semiconductor innovation across various areas, from graphics architecture to advanced packaging. "David, Nathan, Suresh, Ben and Ralph - whose engineering contributions have already left an indelible mark on our industry - represent the best of our innovation culture," said Mark Papermaster, chief technology officer and executive vice president of Technology and Engineering at AMD. "Their appointments to Corporate Fellow will enable AMD to innovate in new dimensions as we work to deliver the most significant breakthroughs in high-performance computing in the decade ahead."

Appointment to AMD Corporate Fellow is an honor bestowed on the most accomplished AMD innovators. AMD Corporate Fellows are appointed after a rigorous review process that assesses not only specific technical contributions to the company, but also involvement in the industry, mentoring of others and improving the long-term strategic position of the company. Currently, only 13 engineers at AMD hold the title of Corporate Fellow.

The unified shader (stream processor) counts of AMD's upcoming second- and third-largest GPUs based on the RDNA3 graphics architecture, have been leaked in some ROCm code, discovered by Kepler_L2 on Twitter. The "performance.hpp" file references "Navi 32" with a compute unit count of 60, and the "Navi 33" with 32 compute units. We know from the "Navi 31" specifications that an RDNA3 compute unit still amounts to 64 stream processors (although with significant IPC uplifts over the RDNA2 stream processor due to dual-instruction issue-rate).

60 compute units would give the "Navi 32" silicon a stream processor count of 3,840, a 50% numerical increase over the 2,560 of its predecessor, the "Navi 22," powering graphics cards such as the Radeon RX 6750 XT. Meanwhile, the 32 CU count of the "Navi 33" amounts to 2,048 stream processors, which is numerically unchanged from that of the "Navi 23" powering the RX 6650 XT. The new RDNA3 compute unit has significant changes over RDNA2, besides the dual-issue stream processors—it gets second-generation Ray Accelerators, and two AI accelerators for matrix-multiplication.

AMD today announced it is joining the newly created PyTorch Foundation as a founding member. The foundation, which will be part of the non-profit Linux Foundation, will drive adoption of Artificial Intelligence (AI) tooling by fostering and sustaining an ecosystem of open source projects with PyTorch, the Machine Learning (ML) software framework originally created and fostered by Meta.

As a founding member, AMD joins others in the industry to prioritize the continued growth of PyTorch's vibrant community. Supported by innovations such as the AMD ROCm open software platform, AMD Instinct accelerators, Adaptive SoCs and CPUs, AMD will help the PyTorch Foundation by working to democratize state-of-the-art tools, libraries and other components to make these ML innovations accessible to everyone.

AMD's RDNA3 graphics IP is just around the corner, and we are hearing more information about the upcoming architecture. Historically, as GPUs advance, it is not unusual for companies to add dedicated hardware blocks to accelerate a specific task. Today, AMD engineers have updated the backend of the LLVM compiler to include a new instruction called Wave Matrix Multiply-Accumulate (WMMA). This instruction will be present on GFX11, which is the RDNA3 GPU architecture. With WMMA, AMD will offer support for processing 16x16x16 size tensors in FP16 and BF16 precision formats. With these instructions, AMD is adding new arrangements to support the processing of matrix multiply-accumulate operations. This is closely mimicking the work NVIDIA is doing with Tensor Cores.

AMD ROCm 5.2 API update lists the use case for this type of instruction, which you can see below:

rocWMMA provides a C++ API to facilitate breaking down matrix multiply accumulate problems into fragments and using them in block-wise operations that are distributed in parallel across GPU wavefronts. The API is a header library of GPU device code, meaning matrix core acceleration may be compiled directly into your kernel device code. This can benefit from compiler optimization in the generation of kernel assembly and does not incur additional overhead costs of linking to external runtime libraries or having to launch separate kernels.

rocWMMA is released as a header library and includes test and sample projects to validate and illustrate example usages of the C++ API. GEMM matrix multiplication is used as primary validation given the heavy precedent for the library. However, the usage portfolio is growing significantly and demonstrates different ways rocWMMA may be consumed.

AMD's ROCm compute programming platform—a competitor to NVIDIA's CUDA, dropped support for the "Polaris" graphics architecture, with the latest version 4.5 update. Users on the official ROCm git raised this as an issue assuming it was a bug, to which an official AMD support handle confirmed that the Radeon RX 480 graphics card of the original poster is no longer supported. Another user tested his "Polaris 20" based RX 570, and it isn't supported, either. It's conceivable that the "Polaris 30" based RX 590, a GPU launched in November 2018, isn't supported either. Cutting out a 3-year old graphics architecture from the compute platform sends the wrong message, especially to CUDA users who AMD wants to win over with ROCm. With contemporary GPUs priced out of reach, IT students are left with used older-generation graphics cards, such as those based on "Polaris." NVIDIA CUDA supports GPUs as far back as "Maxwell" (September 2014).

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.

At this year's International Supercomputing 2021 digital event, AMD (NASDAQ: AMD) is showcasing momentum for its AMD EPYC processors and AMD Instinct accelerators across the High Performance Computing (HPC) industry. The company also outlined updates to the ROCm open software platform and introduced the AMD Instinct Education and Research (AIER) initiative. The latest Top500 list showcased the continued growth of AMD EPYC processors for HPC systems. AMD EPYC processors power nearly 5x more systems compared to the June 2020 list, and more than double the number of systems compared to November 2020. As well, AMD EPYC processors power half of the 58 new entries on the June 2021 list.

"High performance computing is critical to addressing the world's biggest and most important challenges," said Forrest Norrod, senior vice president and general manager, data center and embedded systems group, AMD. "With our AMD EPYC processor family and Instinct accelerators, AMD continues to be the partner of choice for HPC. We are committed to enabling the performance and capabilities needed to advance scientific discoveries, break the exascale barrier, and continue driving innovation."