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TSMC to Enter Mass Production of 6th Generation CoWoS Packaging in 2023, up to 12 HBM Stacks

TSMC, the world's leading semiconductor manufacturing company, is rumored to start production of its 6th generation Chip-on-Wafer-on-Substrate (CoWoS) packaging technology. As the silicon scaling is getting ever so challenging, the manufacturers have to come up with a way to get as much performance as possible. That is where TSMC's CoWoS and other chiplet technologies come. They allow designers to integrate many integrated circuits on a single package, making for a cheaper overall product compared to if the product used one big die. So what is so special about 6th generation CoWoS technology from TSMC, you might wonder. The new generation is said to enable a massive 12 stacks of HBM memory on a package. You are reading that right. Imagine if each stack would be an HBM2E variant with 16 GB capacity that would be 192 GB of memory on the package present. Of course, that would be a very expensive chip to manufacture, however, it is just a showcase of what the technology could achieve.

Update 16:44 UTC—The English DigiTimes report indicates that this technology is expected to see mass production in 2023.

Rambus Advances HBM2E Performance to 4.0 Gbps for AI/ML Training Applications

Rambus Inc. (NASDAQ: RMBS), a premier silicon IP and chip provider making data faster and safer, today announced it has achieved a record 4 Gbps performance with the Rambus HBM2E memory interface solution consisting of a fully-integrated PHY and controller. Paired with the industry's fastest HBM2E DRAM from SK hynix operating at 3.6 Gbps, the solution can deliver 460 GB/s of bandwidth from a single HBM2E device. This performance meets the terabyte-scale bandwidth needs of accelerators targeting the most demanding AI/ML training and high-performance computing (HPC) applications.

"With this achievement by Rambus, designers of AI and HPC systems can now implement systems using the world's fastest HBM2E DRAM running at 3.6 Gbps from SK hynix," said Uksong Kang, vice president of product planning at SK hynix. "In July, we announced full-scale mass-production of HBM2E for state-of-the-art computing applications demanding the highest bandwidth available."

NVIDIA Ampere A100 GPU Gets Benchmark and Takes the Crown of the Fastest GPU in the World

When NVIDIA introduced its Ampere A100 GPU, it was said to be the company's fastest creation yet. However, we didn't know how fast the GPU exactly is. With the whopping 6912 CUDA cores, the GPU can pack all that on a 7 nm die with 54 billion transistors. Paired with 40 GB of super-fast HBM2E memory with a bandwidth of 1555 GB/s, the GPU is set to be a good performer. And how fast it exactly is you might wonder? Well, thanks to the Jules Urbach, the CEO of OTOY, a software developer and maker of OctaneRender software, we have the first benchmark of the Ampere A100 GPU.

Scoring 446 points in OctaneBench, a benchmark for OctaneRender, the Ampere GPU takes the crown of the world's fastest GPU. The GeForce RTX 2080 Ti GPU scores 302 points, which makes the A100 GPU up to 47.7% faster than Turing. However, the fastest Turing card found in the benchmark database is the Quadro RTX 8000, which scored 328 points, showing that Turing is still holding well. The result of Ampere A100 was running with RTX turned off, which could yield additional performance if RTX was turned on and that part of the silicon started working.

GIGABYTE Introduces a Broad Portfolio of G-series Servers Powered by NVIDIA A100 PCIe

GIGABYTE, an industry leader in high-performance servers and workstations, announced its G-series servers' validation plan. Following the NVIDIA A100 PCIe GPU announcement today, GIGABYTE has completed the compatibility validation of the G481-HA0 / G292-Z40 and added the NVIDIA A100 to the support list for these two servers. The remaining G-series servers will be divided into two waves to complete their respective compatibility tests soon. At the same time, GIGABYTE also launched a new G492 series server based on the AMD EPYC 7002 processor family, which provides PCIe Gen4 support for up to 10 NVIDIA A100 PCIe GPUs. The G492 is a server with the highest computing power for AI models training on the market today. GIGABYTE will offer two SKUs for the G492. The G492-Z50 will be at a more approachable price point, whereas the G492-Z51 will be geared towards higher performance.

The G492 is GIGABYTE's second-generation 4U G-series server. Based on the first generation G481 (Intel architecture) / G482 (AMD architecture) servers, the user-friendly design and scalability have been further optimized. In addition to supporting two 280 W 2nd Gen AMD EPYC 7002 processors, the 32 DDR4 memory slots support up to 8 TB of memory and maintain data transmission at 3200 MHz. The G492 has built-in PCIe Gen4 switches, which can provide more PCIe Gen4 lanes. PCIe Gen4 has twice the I/O performance of PCIe Gen3 and fully enables the computing power of the NVIDIA A100 Tensor Core GPU, or it can be applied to PCIe storage to help provide a storage upgrade path that is native to the G492.

NVIDIA Announces A100 PCIe Tensor Core Accelerator Based on Ampere Architecture

NVIDIA and partners today announced a new way for interested users to partake in the AI-training capabilities of their Ampere graphics architecture in the form of the A100 PCIe. Diving a little deeper, and as the name implies, this solution differs from the SXM form-factor in that it can be deployed through systems' existing PCIe slots. The change in interface comes with a reduction in TDP from 400 W down to 250 W in the PCIe version - and equivalent reduced performance.

NVIDIA says peak throughput is the same across the SXM and PCIe version of their A100 accelerator. The difference comes in sustained workloads, where NVIDIA quotes the A100 as delivering 10% less performance compared to its SXM brethren. The A100 PCIe comes with the same 2.4 Gbps, 40 GB HBM2 memory footprint as the SXM version, and all other chip resources are the same. We're thus looking at the same 862 mm² silicon chip and 6,192 CUDA cores across both models. The difference is that the PCIe accelerator can more easily be integrated in existing server infrastructure.

AMD Radeon Pro 5600M with HBM2 Benchmarked

Benchmarks of the new Apple-exclusive AMD Radeon Pro 5600M graphics solution by Max Tech reveals that the new GPU is about 50% faster than the Radeon Pro 5500M, and within striking distance of the Radeon Pro Vega 48 found in Apple's 5K iMacs. The Pro 5600M is an Apple-exclusive solution by AMD, based on the "Navi 12" silicon that features a 7 nm GPU die based on the RDNA graphics architecture, flanked by two 4 GB HBM2 memory stacks over a 2048-bit interface. The GPU die features 2,560 stream processors, but clocked differently from Radeon Pro discrete graphics cards based on the "Navi 10" ASIC that uses conventional GDDR6.

The Radeon Pro 5600M solution was found to be 50.1 percent faster than the Radeon Pro 5500M in Geekbench 5 Metal (another Apple-exclusive SKU found in 16-inch MacBook Pros), and just 12.9 percent behind the Radeon Vega 48. The Vega 56 found in iMac Pro is still ahead. Unigine Heaven sees the Pro 5600M being 48.1% faster than the Pro 5500M, and interestingly, faster than Vega 48 by 11.3%. With 2,560 RDNA stream processors, you'd expect more performance, but this card was designed to meet stringent power limits of 50 W, and has significantly lower clock-speeds than "Navi 10" based Radeon Pro graphics cards (1035 MHz max boost engine clock vs. 1930 MHz and 205 W TDP of the Pro W5700). Find more interesting commentary in the Max Tech video presentation.

AMD "Navi 12" Silicon Powering the Radeon Pro 5600M Rendered

Out of the blue, AMD announced its Radeon Pro 5600M mobile discrete graphics solution exclusive for Apple's 16-inch MacBook Pro. It turns out that the Pro 5600M is based on an all new ASIC by AMD, codenamed "Navi 12." This is a multi-chip module, much like "Vega 20," featuring a 7 nm GPU die and two 16 Gbit (4 GB) HBM2 memory stacks sitting on an interposer. While the actual specs of the GPU die on the "Navi 14" aren't known, on the Pro 5600M, it is configured with 40 RDNA compute units amounting to 2,560 stream processors, 160 TMUs, and possibly 64 ROPs.

The engine clock of the Pro 5600M is set at up to 1035 MHz. The HBM2 memory is clocked at 1.54 Gbps, which at the 2048-bit bus width, translates to 394 GB/s of memory bandwidth. There are two big takeaways from this expensive-looking ASIC design: a significantly smaller PCB footprint compared to a "Navi 10" ASIC with its eight GDDR6 memory chips; and a significantly lower power envelope. AMD rates the typical power at just 50 W. In the render below, the new ASIC is shown next to a "Navi 14" ASIC that power RX/Pro 5500-series SKUs.

New AMD Radeon Pro 5600M Mobile GPU Brings Desktop-Class Graphics Performance and Enhanced Power Efficiency to 16-inch MacBook Pro

AMD today announced availability of the new AMD Radeon Pro 5600M mobile GPU for the 16-inch MacBook Pro. Designed to deliver desktop-class graphics performance in an efficient mobile form factor, this new GPU powers computationally heavy workloads, enabling pro users to maximize productivity while on-the-go.

The AMD Radeon Pro 5600M GPU is built upon industry-leading 7 nm process technology and advanced AMD RDNA architecture to power a diverse range of pro applications, including video editing, color grading, application development, game creation and more. With 40 compute units and 8 GB of ultra-fast, low-power High Bandwidth Memory (HBM2), the AMD Radeon Pro 5600M GPU delivers superfast performance and excellent power efficiency in a single GPU package.

NVIDIA Tesla A100 "Ampere" AIC (add-in card) Form-Factor Board Pictured

Here's the first picture of a Tesla A100 "Ampere" AIC (add-in card) form-factor board, hot on the heals of the morning big A100 reveal. The AIC card is a bare PCB, which workstation builders will add compatible cooling solutions on. The PCB features the gigantic GA100 processor with its six HBM2E stacks, in the center, surrounded by VRM components, and I/O on three sides. On the bottom side, you will find a conventional PCI-Express 4.0 x16 host interface. Above it, are NVLink fingers. The rear I/O has high-bandwidth network interfaces (likely 200 Gbps InfiniBand), by Mellanox. The tail end has hard points for 12 V power input. Find juicy details of the GA100 in our older article.

NVIDIA Tesla A100 GPU Pictured

Thanks to the sources of VideoCardz, we now have the first picture of the next-generation NVIDIA Tesla A100 graphics card. Designed for computing oriented applications, the Tesla A100 is a socketed GPU designed for NVIDIA's proprietary SXM socket. In a post few days ago, we were suspecting that you might be able to fit the Tesla A100 GPU in the socket of the previous Volta V100 GPUs as it is a similar SXM socket. However, the mounting holes have been re-arranged and this one requires a new socket/motherboard. The Tesla A100 GPU is based on GA100 GPU die, which we don't know specifications of. From the picture, we can only see that there is one very big die attached to six HBM modules, most likely HBM2E. Besides that everything else is unknown. More details are expected to be announced today at the GTC 2020 digital keynote.
NVIDIA Tesla A100

AMD Announces Radeon Pro VII Graphics Card, Brings Back Multi-GPU Bridge

AMD today announced its Radeon Pro VII professional graphics card targeting 3D artists, engineering professionals, broadcast media professionals, and HPC researchers. The card is based on AMD's "Vega 20" multi-chip module that incorporates a 7 nm (TSMC N7) GPU die, along with a 4096-bit wide HBM2 memory interface, and four memory stacks adding up to 16 GB of video memory. The GPU die is configured with 3,840 stream processors across 60 compute units, 240 TMUs, and 64 ROPs. The card is built in a workstation-optimized add-on card form-factor (rear-facing power connectors and lateral-blower cooling solution).

What separates the Radeon Pro VII from last year's Radeon VII is full double precision floating point support, which is 1:2 FP32 throughput compared to the Radeon VII, which is locked to 1:4 FP32. Specifically, the Radeon Pro VII offers 6.55 TFLOPs double-precision floating point performance (vs. 3.36 TFLOPs on the Radeon VII). Another major difference is the physical Infinity Fabric bridge interface, which lets you pair up to two of these cards in a multi-GPU setup to double the memory capacity, to 32 GB. Each GPU has two Infinity Fabric links, running at 1333 MHz, with a per-direction bandwidth of 42 GB/s. This brings the total bidirectional bandwidth to a whopping 168 GB/s—more than twice the PCIe 4.0 x16 limit of 64 GB/s.

Fujitsu Completes Delivery of Fugaku Supercomputer

Fujitsu has today officially completed the delivery of the Fugaku supercomputer to the Riken scientific research institute of Japan. This is a big accomplishment as the current COVID-19 pandemic has delayed many happenings in the industry. However, Fujitsu managed to play around that and deliver the supercomputer on time. The last of 400 racks needed for the Fugaku supercomputer was delivered today, on May 13th, as it was originally planned. The supercomputer is supposed to be fully operational starting on the physical year of 2021, where the installation and setup will be done before.

As a reminder, the Fugaku is an Arm-based supercomputer consisting out of 150 thousand A64FX CPUs. These CPUs are custom made processors by Fujitsu based on Arm v8.2 ISA, and they feature 48 cores built on TSMC 7 nm node and running above 2 GHz. Packing 8.786 billion transistors, this monster chips use HBM2 memory instead of a regular DDR memory interface. Recently, a prototype of the Fugaku supercomputer was submitted to the Top500 supercomputer list and it came on top for being the most energy-efficient of all, meaning that it will be as energy efficient as it will be fast. Speculations are that it will have around 400 PetaFlops of general compute power for Dual-Precision workloads, however, for the specific artificial intelligence applications, it should achieve ExaFLOP performance target.
K SuperComputer

Micron to Launch HBM2 Memory This Year

Micron Technologies, in the latest earnings report, announced that they will start shipping High-Bandwidth Memory 2 (HBM2) DRAM. Used for high-performance graphics cards, server processors and all kinds of processors, HBM2 memory is wanted and relatively expensive solution, however, when Micron enters the market of its manufacturing, prices, and the market should adjust for the new player. Previously, only SK-Hynix and Samsung were manufacturing the HBM2 DRAM, however, Micron will join them and they will again form a "big-three" pact that dominates the memory market.

Up until now, Micron used to lay all hopes on its proprietary Hybrid Memory Cube (HMC) DRAM type, which didn't gain much traction from customers and it never really took off. Only a few rare products used it, as Fujitsu SPARC64 XIfx CPU used in Fujitsu PRIMEHPC FX100 supercomputer introduced in 2015. Micron announced to suspend works on HMC in 2018 and decided to devote their efforts to GDDR6 and HBM development. So, as a result, we are seeing that they will launch HBM2 DRAM products sometime this year.
Micron HMC High-Bandwidth Memory

Rambus Designs HBM2E Controller and PHY

Rambus, a maker of various Interface IP solutions, today announced the latest addition to its high-speed memory interface IP product portfolio in form of High Bandwidth Memory 2E (HBM2E) controller and physical layer (PHY) IP solution. The two IPs are enabling customers to completely integrate the HBM2E memory into their products, given that Rambus provides a complete solution for controlling and interfacing the memory. The design that Ramus offers can support for 12-high DRAM stacks of up to 24 Gb devices, making for up to 36 GB of memory per 3D stack. This single 3D stack is capable of delivering 3.2 Gbps over a 1024-bit wide interface, delivering 410 GB/s of bandwidth per stack.

The HBM2E controller core is DFI 3.1 compatible and has support for logic interfaces like AXI, OCP, or a custom one, so the customer can choose a way to integrate this core in their design. With a purchase of their HBM2E IP, Rambus will provide source code written in Hardware Description Language (HDL) and GDSII file containing the layout of the interface.

AMD Announces the CDNA and CDNA2 Compute GPU Architectures

AMD at its 2020 Financial Analyst Day event unveiled its upcoming CDNA GPU-based compute accelerator architecture. CDNA will complement the company's graphics-oriented RDNA architecture. While RDNA powers the company's Radeon Pro and Radeon RX client- and enterprise graphics products, CDNA will power compute accelerators such as Radeon Instinct, etc. AMD is having to fork its graphics IP to RDNA and CDNA due to what it described as market-based product differentiation.

Data centers and HPCs using Radeon Instinct accelerators have no use for the GPU's actual graphics rendering capabilities. And so, at a silicon level, AMD is removing the raster graphics hardware, the display and multimedia engines, and other associated components that otherwise take up significant amounts of die area. In their place, AMD is adding fixed-function tensor compute hardware, similar to the tensor cores on certain NVIDIA GPUs.
AMD Datacenter GPU Roadmap CDNA CDNA2 AMD CDNA Architecture AMD Exascale Supercomputer

AMD Radeon Instinct MI100 "Arcturus" Hits the Radar, We Have its BIOS

AMD's upcoming large post-Navi graphics chip, codenamed "Arcturus," will debut as "Radeon Instinct MI100", which is an AI-ML accelerator under the Radeon Instinct brand, which AMD calls "Server Accelerators." TechPowerUp accessed its BIOS, which is now up on our VGA BIOS database. The card goes with the device ID "0x1002 0x738C," which confirms "AMD" and "Arcturus,". The BIOS also confirms that memory size is at a massive 32 GB HBM2, clocked at 1000 MHz real (possibly 1 TB/s bandwidth, if memory bus width is 4096-bit).

Both Samsung (KHA884901X) and Hynix memory (H5VR64ESA8H) is supported, which is an important capability for AMD's supply chain. From the ID string "MI100 D34303 A1 XL 200W 32GB 1000m" we can derive that the TDP limit is set to a surprisingly low 200 W, especially considering this is a 128 CU / 8,192 shader count design. Vega 64 and Radeon Instinct MI60 for comparison have around 300 W power budget with 4,096 shaders, 5700 XT has 225 W with 2560 shaders, so either AMD achieved some monumental efficiency improvements with Arcturus or the whole design is intentionally running constrained, so that AMD doesn't reveal their hand to these partners, doing early testing of the card.

Samsung Launches 3rd-Generation "Flashbolt" HBM2E Memory

Samsung Electronics, the world leader in advanced memory technology, today announced the market launch of 'Flashbolt', its third-generation High Bandwidth Memory 2E (HBM2E). The new 16-gigabyte (GB) HBM2E is uniquely suited to maximize high performance computing (HPC) systems and help system manufacturers to advance their supercomputers, AI-driven data analytics and state-of-the-art graphics systems in a timely manner.

"With the introduction of the highest performing DRAM available today, we are taking a critical step to enhance our role as the leading innovator in the fast-growing premium memory market," said Cheol Choi, executive vice president of Memory Sales & Marketing at Samsung Electronics. "Samsung will continue to deliver on its commitment to bring truly differentiated solutions as we reinforce our edge in the global memory marketplace."

NVIDIA Unveils Tesla V100s Compute Accelerator

NVIDIA updated its compute accelerator product stack with the new Tesla V100s. Available only in the PCIe add-in card (AIC) form-factor for now, the V100s is positioned above the V100 PCIe, and is equipped with faster memory, besides a few silicon-level changes (possibly higher clock-speeds), to facilitate significant increases in throughput. To begin with, the V100s is equipped with 32 GB of HBM2 memory across a 4096-bit memory interface, with higher 553 MHz (1106 MHz effective) memory clock, compared to the 876 MHz memory clock of the V100. This yields a memory bandwidth of roughly 1,134 GB/s compared to 900 GB/s of the V100 PCIe.

NVIDIA did not detail changes to the GPU's core clock-speed, but mentioned the performance throughput numbers on offer: 8.2 TFLOP/s double-precision floating-point performance versus 7 TFLOP/s on the original V100 PCIe; 16.4 TFLOP/s single-precision compared to 14 TFLOP/s on the V100 PCIe; and 130 TFLOP/s deep-learning ops versus 112 TFLOP/s on the V100 PCIe. Company-rated power figures remain unchanged at 250 W typical board power. The company didn't reveal pricing.

Cray and Fujitsu Partner to Power Supercomputing in the Exascale Era

Global supercomputer leader Cray, a Hewlett Packard Enterprise company, and leading Japanese information and communication technology company Fujitsu, today announced a partnership to offer high performance technologies for the Exascale Era. Under the alliance agreement, Cray is developing the first-ever commercial supercomputer powered by the Fujitsu A64FX Arm -based processor with high-memory bandwidth (HBM) and supported on the proven Cray CS500 supercomputer architecture and programming environment. Initial customers include Los Alamos National Laboratory, Oak Ridge National Laboratory, RIKEN Center for Computational Science, Stony Brook University, and University of Bristol. As part of this new partnership, Cray and Fujitsu will explore engineering collaboration, co-development, and joint go-to-market to meet customer demand in the supercomputing space.

"Our partnership with Fujitsu means customers now have a broader choice of processor technology to address their pressing computational needs," said Fred Kohout, senior vice president and CMO at Cray, a Hewlett Packard Enterprise company. "We are delivering the development-to-deployment experience customers have come to expect from Cray, including exploratory development to the Cray Programming Environment (CPE) for Arm processors to optimize performance and scalability with additional support for Scalable Vector Extensions and high bandwidth memory."

GLOBALFOUNDRIES and SiFive to Deliver Next Level of High Bandwidth Memory on 12LP

GLOBALFOUNDRIES (GF ) and SiFive, Inc. announced today at GLOBALFOUNDRIES Technology Conference (GTC) in Taiwan that they are working to extend high DRAM performance levels with High Bandwidth Memory (HBM2E) on GF's recently announced 12LP+ FinFET solution, with 2.5D packaging design services to enable fast time-to-market for Artificial Intelligence (AI) applications.

In order to achieve the capacity and bandwidth for data-intensive AI training applications, system designers are challenged with squeezing more bandwidth into a smaller area while maintaining a reasonable power profile. SiFive's customizable high bandwidth memory interface on GF's 12LP platform and 12LP+ solution will enable easy integration of high bandwidth memory into a single System-on-Chip (SoC) solutions to deliver fast, power-efficient data processing for AI applications in the computing and wired infrastructure markets.

SK hynix Inc. Reports Third Quarter 2019 Results

SK hynix Inc. today announced financial results for its third quarter 2019 ended on September 30, 2019. The consolidated third quarter revenue was 6.84 trillion won while the operating profit amounted to 473 billion won and the net income 495 billion won. Operating margin and net margin for the quarter was 7%.

The revenue in the third quarter increased by 6% quarter-over-quarter (QoQ) as demand began to pick up. However, the operating profit fell by 26% QoQ as DRAM unit cost reduction was not enough to offset the price drop. DRAM bit shipments increased by 23% QoQ as the Company actively responded to the new products in the mobile market and purchases from some data center customers also increased. DRAM prices remained weak during the quarter, leading to a 16% drop in the average selling price, with the decline smaller than the previous quarter.

Samsung Develops Industry's First 12-Layer 3D-TSV Chip Packaging Technology

Samsung Electronics Co., Ltd., a world leader in advanced semiconductor technology, today announced that it has developed the industry's first 12-layer 3D-TSV (Through Silicon Via) technology. Samsung's new innovation is considered one of the most challenging packaging technologies for mass production of high-performance chips, as it requires pinpoint accuracy to vertically interconnect 12 DRAM chips through a three-dimensional configuration of more than 60,000 TSV holes, each of which is one-twentieth the thickness of a single strand of human hair.

The thickness of the package (720 µm) remains the same as current 8-layer High Bandwidth Memory-2 (HBM2) products, which is a substantial advancement in component design. This will help customers release next-generation, high-capacity products with higher performance capacity without having to change their system configuration designs. In addition, the 3D packaging technology also features a shorter data transmission time between chips than the currently existing wire bonding technology, resulting in significantly faster speed and lower power consumption.

AMD "Navi 14" and "Navi 12" GPUs Detailed Some More

The third known implementation of AMD's "Navi" generation of GPUs with RDNA architecture is codenamed "Navi 14." This 7 nm chip is expected to be a cut-down, mainstream chip designed to compete with a spectrum of NVIDIA GeForce GTX 16-series SKUs, according to a 3DCenter.org report. The same report sheds more light on the larger "Navi 12" GPU that could power faster SKUs competing with the likes of the GeForce RTX 2080 and RTX 2080 Super. The two follow the July launch of the architecture debut with "Navi 10." There doesn't appear to be any guiding logic behind the numerical portion of the GPU codename. When launched, the pecking order of the three Navi GPUs will be "Navi 12," followed by "Navi 10," and "Navi 14."

"Navi 14" is expected to be the smallest of the three, with an estimated 170 mm² die-area, about 24 RDNA compute units (1,536 stream processors), and expected to feature a 128-bit wide GDDR6 memory interface. It will be interesting to see how AMD carves out an SKU that can compete with the GTX 1660 Ti, which has 6 GB of 192-bit GDDR6 memory. The company would have to wait for 16 Gbit (2 GB) GDDR6 memory chips, or piggy-back eight 8 Gbit chips to achieve 8 GB, or risk falling short of recommended system requirements of several games at 1080p, if it packs just 4 GB of memory.

Intel Ships Stratix 10 DX FPGAs, VMWare Among Early Partners

Intel today announced shipments of new Intel Stratix 10 DX field programmable gate arrays (FPGA). The new FPGAs are designed to support Intel Ultra Path Interconnect (Intel UPI), PCI-Express (PCIe) Gen4 x16 and a new controller for Intel Optane technology to provide flexible, high-performance acceleration. VMware is one of many early access program participants.

"Intel Stratix 10 DX FPGAs are the first FPGAs designed to combine key features that dramatically boost acceleration of workloads in the cloud and enterprise when used with Intel's portfolio of data center solutions. No other FPGA currently offers this combination of features for server designs based on future select Intel Xeon Scalable processors," said David Moore, Intel vice president and general manager, FPGA and Power Products, Network and Custom Logic Group.

Control Can Use Up to 18.5GB of Video Memory

"Control" by Remedy is the season's hottest AAA release, not just because it's an above-average story-driven action RPG, but also because it's an eye candy-shop. With the ability to use NVIDIA RTX real-time raytracing across a multitude of features, the game is particularly heavy on graphics hardware. Tweaktown tested the game's stability at extremely high display resolutions, including 8K, and found that the game can use up to 18.5 GB of video memory, when running in DirectX 12 with RTX enabled. There's only one client-segment graphics card capable of that much memory, the $2,499 NVIDIA TITAN RTX, which ships with 24 GB of GDDR6 memory. Its nearest client-segment neighbor is the AMD Radeon VII, but it only packs 16 GB of HBM2.

When a game needs more video memory than your graphics card has, Windows has an elaborate memory management system that sheds some of that memory onto your system's main memory, and the swap file progressively (at reduced performance, of course). Video memory usage drops like a rock between 8K and 4K UHD (which is 1/4th the pixels as 8K). With all RTX features enabled and other settings maxed out, "Control" only uses 8.1 GB of video memory. What this also means is that video cards with just 8 GB of memory are beginning fall short of what it takes to game at 4K. The $699 GeForce RTX 2080 Super only has 8 GB. The RTX 2080 Ti, with its 11 GB of memory has plenty of headroom and muscle. Find other interesting observations in the source link below.
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