Subject: Graphics Cards | June 5, 2018 - 11:58 PM | Tim Verry
Tagged: Vega, machine learning, instinct, HBM2, gpu, computex 2018, computex, amd, 7nm
AMD showed off its first 7nm GPU in the form of the expected AMD Radeon Instinct RX Vega graphics product and RX Vega GPU with 32GB of HBM2 memory. The new GPU uses the Vega architecture along with the open source ecosystem built by AMD to enable both graphics and GPGPU workloads. AMD demonstrated using the 7nm RX Vega GPU for ray tracing in a cool demo that showed realistic reflections and shadows being rendered on a per pixel basis in a model. Granted, we are still a long way away from seeing that kind of detail in real time gaming, but is still cool to see glimpses of that ray traced future.
According to AMD, the 32GB of HBM2 memory will greatly benefit creators and enterprise clients that need to work with large datasets and be able to quickly make changes and updates to models before doing a final render. The larger memory buffer will also help in HPC applications with more big data databases being able to be kept close to the GPU for processing using the wide HBM2 memory bus. Further, HBM2 has physical size and energy efficiency benefits which will pique the interest of datacenters focused on maximizing TCO numbers.
Dr. Lisa Su came on state towards the end of the 7nm Vega demonstration to show off the GPU in person, and you can see that it is rather tiny for the compute power it provides! It is shorter than the two stacks of HBM2 dies on either side, for example.
Of course AMD did not disclose all the nitty-gritty specifications of the new machine learning graphics card that enthusiasts want to know. We will have to wait a bit longer for that information unfortunately!
As for other 7nm offerings? As Ryan talked about during CES in January, 2018 will primarily be the year for the machine learning-focused Radeon Instinct RX Vega 7nm GPU, with other consumer-focused GPUs using the smaller process node likely coming out in 2019. Whether those 7nm GPUs in 2019 will be a refreshed Vega or the new Navi is still up for debate, however AMD's graphics roadmap certainly doesn't rule out Navi as a possibility. In any case, AMD did state during the livestream that it intends to release a new GPU every year with the GPUs alternating between new architecture and new process node.
What are your thoughts on AMD's graphics roadmap and its first 7nm Vega GPU?
Subject: General Tech | June 21, 2017 - 12:21 PM | Jeremy Hellstrom
Tagged: EPYC, amd, instinct
[H]ard|OCP were at AMD's launch of the new EPYC family of server CPUs and captured the presentation and slide deck in a series of photos you can take a look at right here. They cover the work being done with HP and Dell, as well as with internet service providers such as Microsoft's Azure platform and China's Baidu. They even give you a look at some of the products which will be launched running on Supermicro platforms. AMD is looking very attractive to server builders at the moment, a feeling you may already have garnered from reading Ryan's take on EPYC.
"AMD held it official EPYC enterprise CPU launch today in Austin, TX. If you are not aware of EPYC, it is quite simply AMD's effort to get back into the datacenters that are now firmly held by Intel Xeon processors. What do you get when you take 4 Ryzen 7 CPUs and put those down on a single package with Infinity Fabric? You would be correct, its EPYC."
Here is some more Tech News from around the web:
- AMD's Epyc 7000-series CPUs @ The Tech Report
- AMD EPYC Architecture & Technical Overview @ techPowerUp
- Samsung's 'Magician' for SSDs can let crims run evil code @ The Register
- Acer's mixed reality Windows headset is a thrill ride standing still @ The Inquirer
- The 2017 ASUS ZenBook & VivoBook Laptops Revealed @ TechARP
- Microsoft says Skype outages are over – a few hours too early @ The Register
- Reolink RLC-411WS Wireless Security Camera Review @ OCC
- Arozzi Verona Pro V2 Gaming Chair Review @ NikKTech
Subject: Editorial | December 15, 2016 - 02:18 PM | Alex Lustenberg
Tagged: podcast, zalman, ryzen, note 7, nand, LG, instinct, hdr, DRM, doom, amd
PC Perspective Podcast #428 - 12/8/16
Join us this week as we discuss AMD ReLive, Ryzen, Zalman Keyboards, LG HDR monitors and more!
The URL for the podcast is: http://pcper.com/podcast - Share with your friends!
- iTunes - Subscribe to the podcast directly through the iTunes Store (audio only)
- Google Play - Subscribe to our audio podcast directly through Google Play!
- RSS - Subscribe through your regular RSS reader (audio only)
- MP3 - Direct download link to the MP3 file
Hosts: Allyn Malventano, Josh Walrath, Jeremy Hellstrom, Sebastian Peak
Program length: 1:17:34
Podcast topics of discussion:
Week in Review:
News items of interest:
Hardware/Software Picks of the Week
Subject: Graphics Cards | December 12, 2016 - 04:05 PM | Jeremy Hellstrom
Tagged: vega 10, Vega, training, radeon, Polaris, machine learning, instinct, inference, Fiji, deep neural network, amd
Ryan was not the only one at AMD's Radeon Instinct briefing, covering their shot across NVIDIA's HPC products. The Tech Report just released their coverage of the event and the tidbits which AMD provided about the MI25, MI8 and MI6; no relation to a certain British governmental department. They focus a bit more on the technologies incorporated into GEMM and point out that AMD's top is not matched by an NVIDIA product, the GP100 GPU does not come as an add-in card. Pop by to see what else they had to say.
"Thus far, Nvidia has enjoyed a dominant position in the burgeoning world of machine learning with its Tesla accelerators and CUDA-powered software platforms. AMD thinks it can fight back with its open-source ROCm HPC platform, the MIOpen software libraries, and Radeon Instinct accelerators. We examine how these new pieces of AMD's machine-learning puzzle fit together."
Here are some more Graphics Card articles from around the web:
- The Complete AMD Radeon Instinct Tech Briefing @ Tech ARP
- Chill With Radeon Software Crimson ReLive Edition @ Techgage
- Radeon Software Crimson ReLive Edition—an overview @ The Tech Report
- AMD Radeon Crimson ReLive Drivers @ techPowerUp
- AMD talk to KitGuru about Crimson ReLive
- We retest Radeon Chill 2 The Tech Report
- MSI RX 480 Gaming X 8G Review @ OCC
- NVIDIA GeForce GTX 1080 PCI-Express Scaling @ techPowerUp
AMD Enters Machine Learning Game with Radeon Instinct Products
NVIDIA has been diving in to the world of machine learning for quite a while, positioning themselves and their GPUs at the forefront on artificial intelligence and neural net development. Though the strategies are still filling out, I have seen products like the DIGITS DevBox place a stake in the ground of neural net training and platforms like Drive PX to perform inference tasks on those neural nets in self-driving cars. Until today AMD has remained mostly quiet on its plans to enter and address this growing and complex market, instead depending on the compute prowess of its latest Polaris and Fiji GPUs to make a general statement on their own.
The new Radeon Instinct brand of accelerators based on current and upcoming GPU architectures will combine with an open-source approach to software and present researchers and implementers with another option for machine learning tasks.
The statistics and requirements that come along with the machine learning evolution in the compute space are mind boggling. More than 2.5 quintillion bytes of data are generated daily and stored on phones, PCs and servers, both on-site and through a cloud infrastructure. That includes 500 million tweets, 4 million hours of YouTube video, 6 billion google searches and 205 billion emails.
Machine intelligence is going to allow software developers to address some of the most important areas of computing for the next decade. Automated cars depend on deep learning to train, medical fields can utilize this compute capability to more accurately and expeditiously diagnose and find cures to cancer, security systems can use neural nets to locate potential and current risk areas before they affect consumers; there are more uses for this kind of network and capability than we can imagine.