Pinterest has engineered a strategy to serve its photo-sharing neighborhood extra of the pictures they love.

The social-image service, with greater than 400 million month-to-month energetic customers, has educated greater recommender fashions for improved accuracy at predicting folks’s pursuits.

Pinterest handles lots of of tens of millions of person requests an hour on any given day. And it should additionally slim down related pictures from roughly 300 billion pictures on the positioning to roughly 50 for every particular person.

The final step — rating essentially the most related and interesting content material for everybody utilizing Pinterest — required a leap in acceleration to run heftier fashions, with minimal latency, for higher predictions.

Pinterest has improved the accuracy of its recommender fashions powering folks’s dwelling feeds and different areas, growing engagement by as a lot as 16%.

The leap was enabled by switching from CPUs to NVIDIA GPUs, which may simply be utilized subsequent to different areas, together with promoting pictures, in line with Pinterest.

“Usually we might be pleased with a 2% improve, and 16% is only a starting for dwelling feeds. We see further positive factors — it opens a whole lot of doorways for alternatives,” stated Pong Eksombatchai, a software program engineer at Pinterest.

Transformer fashions able to higher predictions are shaking up industries from retail to leisure and promoting. However their leaps in efficiency positive factors of the previous few years have include a must serve fashions which are some 100x greater as their variety of mannequin parameters and computations skyrockets.

Enormous Inference Positive factors, Identical Infrastructure Price

Like many, Pinterest engineers needed to faucet into state-of-the-art recommender fashions to extend engagement. However serving these huge fashions on CPUs introduced a 100x improve in value and latency. That wasn’t going to take care of its magical person expertise — contemporary and extra interesting pictures — occurring inside a fraction of a second.

“If that latency occurred, then clearly our customers wouldn’t like that very a lot as a result of they must wait endlessly,” stated Eksombatchai. “We’re fairly near the restrict of what we will do on CPU principally.”

The problem was to serve these hundredfold bigger recommender fashions throughout the identical value and latency constraints.

Working with NVIDIA, Pinterest engineers started architectural modifications to optimize their inference pipeline and recommender fashions to allow the transition from CPU to GPU cloud situations. The expertise transition started late final yr and required main modifications to how the corporate manages workloads. The result’s a 100x acquire in inference effectivity on the identical IT price range, assembly their objectives.

“We’re beginning to use actually, actually massive fashions now. And that’s the place the GPU is available in — to assist make these fashions attainable,” Eksombatchai stated.

Tapping Into cuCollections 

Switching from CPUs to GPUs required rethinking its inference techniques structure. Amongst different points, engineers needed to change how they ship workloads to their inference servers. Fortuitously, there are instruments to help in making the transition simpler.

The Pinterest inference server constructed for CPUs needed to be altered as a result of it was set as much as ship smaller batch sizes to its servers. GPUs can deal with a lot bigger workloads, so it’s essential to arrange bigger batch requests to extend effectivity.

One space the place this comes into play is with its embedding desk lookup module. Embedding tables are used to trace interactions between varied context-specific options and pursuits of person profiles. They’ll observe the place you navigate, and what folks Pin on Pinterest, share or quite a few different actions, serving to refine predictions on what customers may wish to click on on subsequent.

They’re used to incrementally study person choice primarily based on context so as to make higher content material suggestions to these utilizing Pinterest. Its embedding desk lookup module required two computation steps repeated lots of of occasions due to the variety of options tracked.

Pinterest engineers significantly decreased this variety of operations utilizing a GPU-accelerated concurrent hash desk from NVIDIA cuCollections. They usually arrange a customized consolidated embedding lookup module so they may merge requests right into a single lookup. Higher outcomes had been seen instantly.

“Utilizing cuCollections helped us to take away bottlenecks,” stated Eksombatchai.

Enlisting CUDA Graphs

Pinterest relied on CUDA Graphs to eradicate what was remaining of the small batch operations, additional optimizing its inference fashions.

CUDA Graphs helps cut back the CPU interactions when launching on GPUs. They’re  designed to allow workloads to be outlined as graphs relatively than single operations. They supply a mechanism to launch a number of GPU operations by means of a single CPU operation, lowering CPU overheads.

Pinterest enlisted CUDA Graphs to characterize the mannequin inference course of as a static graph of operation as a substitute of as these individually scheduled. This enabled the computation to be dealt with as a single unit with none kernel launching overhead.

The corporate now helps CUDA Graph as a brand new backend of its mannequin server. When a mannequin is first loaded, the mannequin server runs the mannequin inference as soon as to construct the graph occasion. This graph  can then be run repeatedly in inference to point out content material on its app or website.

Implementing CUDA Graphs helped Pinterest to considerably cut back inference latency of its recommender fashions, in line with its engineers.

GPUs have enabled Pinterest to do one thing that was unimaginable with CPUs on the identical price range, and by doing this they will make modifications which have a direct impression on varied enterprise metrics.

Find out about Pinterest’s GPU-driven inference and optimizations at its GTC session, Serving 100x Bigger Recommender Models, and in the Pinterest Engineering blog.  

Register for GTC, working Sept. 19-22, without cost to attend periods with NVIDIA and dozens of business leaders.

Think about climbing to a lake on a summer time day — sitting beneath a shady tree and watching the water gleam beneath the solar.

On this scene, the variations between gentle and shadow are examples of direct and oblique lighting.

The solar shines onto the lake and the timber, making the water appear like it’s shimmering and the leaves seem brilliant inexperienced. That’s direct lighting. And although the timber solid shadows, daylight nonetheless bounces off the bottom and different timber, casting gentle on the shady space round you. That’s oblique lighting.

For pc graphics to immerse viewers in photorealistic environments, it’s necessary to precisely simulate the conduct of sunshine to attain the right steadiness of direct and oblique lighting.

What Is Direct and Oblique Lighting?

Gentle shining onto an object is named direct lighting.

It determines the colour and amount of sunshine that reaches a floor from a lightweight supply, however ignores all gentle which will arrive on the floor from another sources, corresponding to after reflection or refraction. Direct lighting additionally determines the quantity of the sunshine that’s absorbed and mirrored by the floor itself.

Gentle bouncing off a floor, illuminating different objects is named oblique lighting. It arrives at surfaces from every little thing besides gentle sources. In different phrases, oblique lighting determines the colour and amount of all different gentle that arrives at a floor. Mostly, oblique gentle is mirrored from one floor onto different surfaces.

Oblique lighting typically tends to be harder and costly to compute than direct lighting. It’s because there’s a considerably bigger variety of paths that gentle can take between the sunshine emitter and the observer.

What Is World Illumination?

World illumination is the method of computing the colour and amount of all gentle — each direct and oblique — that’s on seen surfaces in a scene.

Precisely simulating all forms of oblique gentle is extraordinarily troublesome, particularly if the scene consists of advanced supplies corresponding to glass, water and glossy metals — or if the scene has scattering in clouds, smoke, fog or different parts often known as volumetric media.

Consequently, real-time graphics options for world illumination are sometimes restricted to computing a subset of the oblique gentle — generally for surfaces with diffuse (aka matte) supplies.

How Are Direct and Oblique Lighting Computed? 

Many algorithms can be utilized for computing direct lighting, all of which have strengths and weaknesses. For instance, if the scene has a single gentle and no shadows, direct illumination is trivial to compute, nevertheless it gained’t look very sensible. Alternatively, when a scene has a number of gentle sources, processing all of them for every floor can turn out to be costly.

To deal with these points, optimized algorithms and shading methods have been developed, corresponding to deferred or clustered shading. These algorithms cut back the variety of floor and lightweight interactions to be computed.

Shadows could be added by way of quite a few methods, together with shadow maps, stencil shadow volumes and ray tracing.

Shadow mapping has two steps. First, the scene is rendered from the sunshine’s standpoint right into a particular texture referred to as the shadow map. Then, the shadow map is used to check whether or not surfaces seen on the display are additionally seen from the sunshine’s standpoint. Shadow maps include many limitations and artifacts, and rapidly turn out to be costly because the variety of lights within the scene will increase.

Stencil shadow volumes are primarily based on extruding scene geometry away from the sunshine, and rendering that extruded geometry into the stencil buffer. The contents of the stencil buffer are then used to find out if a given floor on the display is in shadow or not. Stencil shadows are at all times sharp, unnaturally so, however they don’t undergo from widespread shadow map issues.

Till the introduction of NVIDIA RTX technology, ray tracing was too expensive to make use of when computing shadows. Ray tracing is a technique of rendering in graphics that simulates the bodily conduct of sunshine. Tracing the rays from a floor on the display to a lightweight permits for the computation of shadows, however this may be difficult if the sunshine comes from one level. And ray-traced shadows can rapidly get costly if there are a lot of lights within the scene.

Extra environment friendly sampling strategies have been developed to scale back the variety of rays required to compute comfortable shadows from a number of lights. One instance is an algorithm referred to as ReSTIR, which calculates direct lighting from hundreds of thousands of lights and shadows with ray tracing at interactive body charges.

What Is Path Tracing?

For oblique lighting and world illumination, much more strategies exist. Probably the most simple is named path tracing, the place random gentle paths are simulated for every seen floor. A few of these paths attain lights and contribute to the completed scene, whereas others don’t.

Path tracing is essentially the most correct technique able to producing outcomes that absolutely characterize lighting in a scene, matching the accuracy of mathematical fashions for supplies and lights. Path tracing could be very costly to compute, nevertheless it’s thought-about the “holy grail” of real-time graphics.

How Does Direct and Oblique Lighting Have an effect on Graphics?

Direct lighting gives the essential look of realism, and oblique lighting makes scenes look richer and extra pure.

A technique oblique lighting has been utilized in many video video games is thru omnipresent ambient gentle. Any such gentle could be fixed, or differ spatially over gentle probes organized in a grid sample. It will also be rendered right into a texture that’s wrapped round static objects in a scene — this technique is named a “gentle map.”

Usually, ambient gentle is shadowed by a perform of geometry across the floor referred to as ambient occlusion, which helps enhance the picture realism.

Examples of Direct Lighting, Oblique Lighting and World Illumination

Direct and oblique lighting has been current, in some kind, in virtually each 3D recreation because the Nineties. Beneath are some milestones of how lighting has been carried out in well-liked titles:

• 1993: Doom showcased one of many first examples of dynamic lighting. The sport may differ the sunshine depth per sector, which made textures lighter or darker, and was used to simulate dim and brilliant areas or flickering lights.

• 1995: Quake launched gentle maps, which have been pre-computed for every stage within the recreation. The sunshine maps may modulate the ambient gentle depth.
• 1997: Quake II added colour to the sunshine maps, in addition to dynamic lighting from projectiles and explosions.
• 2001: Silent Hill 2 showcased per-pixel lighting and shadow mapping. Shrek used deferred lighting and stencil shadows.
• 2007: Crysis confirmed dynamic screen-space ambient occlusion, which makes use of pixel depth to present a way of adjustments in lighting.

• 2008: Quake Wars: Ray Traced turned the primary recreation tech demo to make use of ray-traced reflections.
• 2011: Crysis 2 turned the primary recreation to incorporate screen-space reflections, which is a well-liked method for reusing screen-space information to calculate reflections.
• 2016: Rise of the Tomb Raider turned the primary recreation to make use of voxel-based ambient occlusion.
• 2018: Battlefield V turned the primary business recreation to make use of ray-traced reflections.
• 2019: Q2VKPT turned the primary recreation to implement path tracing, which was later refined in Quake II RTX.
• 2020: Minecraft with RTX used path tracing with RTX.

What’s Subsequent for Lighting in Actual-Time Graphics?

Actual-time graphics are transferring towards a extra full simulation of sunshine in scenes with growing complexity.

ReSTIR dramatically expands the chances of artists to make use of a number of lights in video games. Its newer variant, ReSTIR GI, applies the identical concepts towards world illumination, enabling path tracing with extra bounces and fewer approximations. It may possibly additionally render much less noisy pictures sooner. And extra algorithms are being developed to make path tracing sooner and extra accessible.

Utilizing a whole simulation of lighting results with ray tracing additionally implies that the rendered pictures can include some noise. Clearing that noise, or “denoising,” is one other space of energetic analysis.

Extra applied sciences are being developed to assist video games successfully denoise lighting in advanced, extremely detailed scenes with a number of movement at real-time body charges. This problem is being approached from two ends: superior sampling algorithms that generate much less noise and superior denoisers that may deal with more and more troublesome conditions.

Take a look at NVIDIA’s options for direct lighting and indirect lighting, and entry NVIDIA resources for game development.

Be taught extra about graphics with NVIDIA at SIGGRAPH ‘22 and watch the NVIDIA’s special address, offered by NVIDIA CEO and senior leaders, to listen to the newest graphics bulletins.

Progressive applied sciences in AI, digital worlds and digital people are shaping the way forward for design and content material creation throughout each trade. Expertise the newest advances from NVIDIA in all these areas at SIGGRAPH, the world’s largest gathering of pc graphics specialists, operating Aug. 8-11.

On the convention, creators, builders, engineers, researchers and college students will see all the brand new tech and analysis that permits them to raise immersive storytelling, construct sensible avatars and create beautiful 3D digital worlds.

NVIDIA’s special address on Tuesday, Aug. 9, at 9 a.m. PT will function founder and CEO Jensen Huang, together with different senior leaders. Be a part of to get an unique take a look at a few of our most fun work, from award-winning analysis to new AI-powered instruments and options.

Uncover the emergence of the metaverse, and see how customers can construct 3D content material and join photorealistic digital worlds with NVIDIA Omniverse, a computing platform for 3D design collaboration and true-to-reality world simulation. See the superior options which might be powering these 3D worlds, and the way they broaden the realm of creative expression and creativity.

NVIDIA can be presenting over 20 in-person sessions at SIGGRAPH, together with hands-on labs and analysis displays. Discover the session matters beneath to construct your calendar for the occasion:

Constructing 3D Digital Worlds

See how customers can create belongings and construct digital worlds for the metaverse utilizing the facility and flexibility of Universal Scene Description (USD) with this presentation:

Powering the Metaverse

Learn how to speed up complicated 3D workflows and content material creation for the metaverse. Uncover groundbreaking methods to visualise, simulate and code with superior options like NVIDIA Omniverse in periods together with:

• Real-Time Collaboration in Ray-Traced VR. Uncover the latest leaps in {hardware} structure and graphics software program which have made ray tracing at virtual-reality body charges attainable at this session on Monday, Aug. 8, at 5 p.m. PT.
• Material Workflows in Omniverse. Learn to enhance graphics workflows with arbitrary materials shading programs supported in Omniverse at this discuss on Thursday, Aug. 11, at 9 a.m. PT.

Exploring Neural Graphics Analysis

Be taught extra about neural graphics — the unification of AI and graphics — which can make metaverse content material creation accessible to everybody. From 3D belongings to animation, see how AI integration can improve outcomes, automate design selections and unlock new alternatives for creativity within the metaverse. Take a look at the session beneath:

Accelerating Workflows Throughout Industries

Get insights on the newest applied sciences reworking industries, from cloud manufacturing to prolonged actuality. Uncover how main movie studios, cutting-edge startups and different graphics corporations are constructing and supporting their applied sciences with NVIDIA options. Some must-see periods embody:

SIGGRAPH registration is required to attend the in-person occasions. Periods will even be accessible the next day to watch on demand from our web site.

Many NVIDIA companions will attend SIGGRAPH, showcasing demos and presenting on matters similar to AI and digital worlds. Download this event map to be taught extra.

And tune into the worldwide premiere of The Art of Collaboration: NVIDIA, Omniverse and GTC on Wednesday, Aug. 10, at 10 a.m. PT. The documentary shares the story of the engineers, artists and researchers who pushed the bounds of NVIDIA GPUs, AI and Omniverse to ship the beautiful GTC keynote final spring.

Be a part of NVIDIA at SIGGRAPH to be taught extra, and watch NVIDIA’s special address to listen to the newest on graphics, AI and digital worlds.

Autonomous automobiles are probably the most advanced AI challenges of our time. For AVs to function safely in the actual world, the networks operating inside them should come collectively as an intricate symphony, which requires intensive coaching, testing and validation on huge quantities of knowledge.

Clément Farabet, vice chairman of AI infrastructure at NVIDIA, is a proverbial maestro behind the AV improvement orchestra. He’s making use of almost 15 years of expertise in deep studying — together with constructing Twitter’s AI machine — to show neural networks the best way to understand and react to the world round them.

Farabet sat down with NVIDIA’s Katie Burke Washabaugh on the most recent episode of the AI Podcast to debate how the early days of deep studying led to at this time’s flourishing AV {industry}, and the way he’s approaching deep neural community improvement.

Tapping into the NVIDIA SaturnV supercomputer, Farabet is designing a extremely scalable information manufacturing facility to ship clever transportation within the close to time period, whereas looking forward to the subsequent frontiers in AI.

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Bringing new AI and robotics purposes and merchandise to market, or supporting present ones, may be difficult for builders and enterprises.

The NVIDIA Jetson AGX Orin 32GB production module — out there now — is right here to assist.

Almost three dozen know-how suppliers within the NVIDIA Partner Network worldwide are providing commercially out there merchandise powered by the brand new module, which gives as much as a 6x efficiency leap over the earlier era.

With a variety of choices from Jetson companions, builders can construct and deploy feature-packed Orin-powered methods sporting cameras, sensors, software program and connectivity fitted to edge AI, robotics, AIoT and embedded purposes.

Manufacturing-ready methods with choices for peripherals allow prospects to deal with challenges in industries from manufacturing, retail and building to agriculture,  logistics, healthcare, good cities, last-mile supply and extra.

Serving to Construct Extra Succesful AI-Pushed Merchandise Quicker 

Historically, builders and engineers have been restricted of their capability to deal with a number of concurrent information streams for advanced utility environments. They’ve confronted strict latency necessities, energy-efficiency constraints, and points with high-bandwidth wi-fi connectivity. And so they want to have the ability to simply handle over-the-air software program updates.

They’ve additionally been pressured to incorporate a number of chips of their designs to harness the compute sources wanted to course of numerous, ever-growing quantities of information.

NVIDIA Jetson AGX Orin overcomes all of those challenges.

The Jetson AGX Orin developer package, able to as much as 275 trillion operations per second, helps a number of concurrent AI utility pipelines with an NVIDIA Ampere structure GPU, next-generation deep learning and vision accelerators, high-speed I/O, and quick reminiscence bandwidth.

With Jetson AGX Orin, prospects can develop options utilizing the most important and most advanced AI fashions to resolve issues corresponding to pure language understanding, 3D notion and multi-sensor fusion.

The 4 Jetson Orin-based manufacturing modules, introduced at GTC, provide prospects a full vary of server-class AI efficiency. The Jetson AGX Orin 32GB module is available to purchase now, whereas the 64GB model will probably be out there in November. Two Orin NX manufacturing modules are coming later this yr.

The manufacturing methods are supported by the NVIDIA Jetson software program stack, which has enabled hundreds of enterprises and thousands and thousands of builders to construct and deploy totally accelerated AI options on Jetson.

On prime of JetPack SDK, which incorporates the NVIDIA CUDA-X accelerated stack, Jetson Orin helps a number of NVIDIA platforms and frameworks corresponding to Isaac for robotics, DeepStream for pc imaginative and prescient, Riva for pure language understanding, TAO Toolkit to speed up mannequin growth with pretrained fashions, and Metropolis, an utility framework, set of developer instruments and companion ecosystem that brings visible information and AI collectively to enhance operational effectivity and security throughout industries.

Prospects are bringing their next-generation edge AI and robotics purposes to market a lot sooner by first emulating any Jetson Orin-based manufacturing module on the Jetson AGX Orin developer package.

Increasing Developer Group and Jetson Accomplice Ecosystem 

Greater than 1 million builders and over 6,000 firms are constructing industrial merchandise on the NVIDIA Jetson edge AI and robotics computing platform to create and deploy autonomous machines and edge AI purposes.

With over 150 members, the rising Jetson ecosystem of companions gives an unlimited vary of assist, together with from firms specialised in AI software program, {hardware} and utility design companies, cameras, sensors and peripherals, developer instruments and growth methods.

Some 32 companions provide commercially out there merchandise, powered by the brand new Jetson AGX Orin module, which might be filled with choices to assist assist cutting-edge purposes and speed up time to market.

Builders in search of carrier boards and full hardware systems will discover a vary of choices from AAEON, Auvidea, Join Tech, MiiVii, Plink-AI, Realtimes and TZTEK to serve their wants.

Over 350 camera and sensor choices can be found from Allied Imaginative and prescient, Appropho, Basler AG, e-Con Methods, Framos, Leopard Imaging, LIPS, Robosense, Shenzhen Sensing, Stereolabs, Thundersoft, Unicorecomm and Velodyne. These can assist difficult indoor/out of doors lighting situations, in addition to capabilities like lidars for mapping, localization and navigation in robotics and autonomous machines.

For complete software program assist like gadget administration, working methods (Yocto & Realtime OS), AI software program and toolkits, builders can look to Allxon, Cogniteam, Concurrent Realtime, Deci AI, DriveU, Novauto, RidgeRun, and Sequitur Labs.

And for connectivity choices, together with WiFi 6/6E, LTE and 5G, builders can take a look at the product choices from Telit, Quectel, Infineon and Silex.

The brand new NVIDIA Jetson AGX Orin 32GB manufacturing module is on the market within the Jetson retailer from retail and distribution partners worldwide.  

Editor’s observe: This submit is a part of our weekly In the NVIDIA Studio collection, which celebrates featured artists, presents inventive ideas and tips, and demonstrates how NVIDIA Studio expertise accelerates inventive workflows. 

3D phenom FESQ joins us Within the NVIDIA Studio this week to share his sensational and surreal animation Double/Sided in addition to an inside look into his inventive workflow.

Double/Sided is deeply private to FESQ, who mentioned the piece “interprets rather well to a sure interval of my life once I was juggling each a programmer profession and an artist profession.”

He candidly admitted “that point was fairly laborious on me with some intense work hours, so I had the fixed lingering feeling that I wanted to decide on one or the opposite.”

The piece eloquently and cleverly shows this duality with flowers representing nature and FESQ’s ardour for creativity, whereas the cranium comprises components of tech, all with a futuristic cyberpunk aesthetic.

Duality Examined

Double/Sided, like most of FESQ’s initiatives, was rigorously researched and concepted, utilizing Figma to create moodboards and collect visible references. Literal stick figures and sketches enable him to put out doable compositions and configurations, scanned into Figma, complementing his moodboard, which ready him to start the 3D stage.

FESQ deployed Cinema 4D to construct out the bottom mannequin for the cranium. Cinema 4D let him choose from widespread GPU-accelerated 3D renderers, comparable to V-Ray, OctaneRender and Redshift, giving him the liberty to modify relying on which renderer is extra advantageous.

As his system is supplied with a GeForce RTX 3080 Ti GPU, the viewport turns into GPU-accelerated, enabling clean interactivity whereas modifying the 3D mannequin. Glad with the look, FESQ turned his consideration in direction of creating supplemental property that have been positioned on the cranium, such because the flowers and electrical emitters. FESQ usually tabs Daz Studio at this level in his initiatives. Whereas not wanted with Double/Sided, Daz presents the largest 3D model library with a big selection of free and premium 3D content material, and artists profit from its RTX-accelerated AI denoiser.

FESQ shortly renders out high-quality recordsdata along with his GPU’s RTX-accelerated NVIDIA Iray renderer, saving beneficial time with out having to attend.

Subsequent, FESQ pivoted to Adobe Substance 3D Painter to use colours and textures. This “is likely to be one of the crucial essential points of my work,” he acknowledged.

And for good purpose, as FESQ is colorblind. One of many tougher points in his inventive work is distinguishing between completely different colours. This makes FESQ’s means to create gorgeous, vibrant artwork all of the extra spectacular.

FESQ then utilized varied colours and light-weight supplies on to his 3D mannequin. NVIDIA RTX and NVIDIA Iray expertise within the viewport enabled him to ideate in actual time and use ray-traced baking for quicker rendering speeds — all accelerated by his GPU.

He returned to Cinema 4D to rig the asset, apply meshes and end animating the scene, leaving last composite work to be accomplished in Adobe After Results.

Realism will be additional enhanced by including correct depth results. For extra insights, watch FESQ’s Studio Session tutorial Using MoGraph to Create Depth in Animations in Cinema 4D & Redshift.

Right here FESQ used the Lumetri Shade impact panel to use professional-quality grading and colour correction instruments to the animation, instantly on his timeline, with GPU-accelerated velocity. The Glow characteristic, additionally GPU accelerated, added the neon mild look that makes Double/Sided merely gorgeous.

For tips about how you can create neon cables like these, try FESQ’s Studio Session tutorial Easily Create Animated Neon Cables in Cinema 4D & Redshift to carry animated items to life.

FESQ couldn’t ponder how he’d full his imaginative and prescient with out his GPU, noting “just about my complete workflow depends on GPU acceleration.”

Artists looking for methods to create surreal landscapes can view FESQ’s Studio Session tutorial Creating Surreal Landscapes Using Cloners in Cinema 4D & Redshift.

Try FESQ’s Instagram for a sampling of his work.

Observe NVIDIA Studio on Instagram, Twitter and Facebook. Entry tutorials on the Studio YouTube channel and get updates instantly in your inbox by subscribing to the NVIDIA Studio newsletter.