A CPU can perform better in some workloads compared to others, depending on its architecture and how it handles (schedules) different instructions. cl-mem is an OpenCL memory benchmark utility. Best gaming motherboard (opens in new tab): The right boards Passing negative parameters to a wolframscript. ensuring that both low-end devices and high-end devices are used to their best of their capability. It is not what you usually want for graphics, and it is not what GPUs could do, say, a decade ago. It offers an unbiased way of testing and comparing the performance of implementations of OpenCL 1.1, a royalty-free standard for heterogenous parallel programming. ^^^^My result in Sierra was a bit higher, but not by much. How fast is your OpenCL? If you intend to run very computationally expensive workloads like CPU rendering or physics simulations, you probably want something with many cores and threads, like the AMD Ryzen 9 5900HX or Intel Core i9-10980HK, both of which have 8 cores and 16 threads. Another major reason is that OpenGL\GLSL are supported only on graphics cards. The benchmarks run in the background and loop asynchronously . This is largely a good thing: only Intel ever got OpenCL 2.0 off the ground. In my little experience, a good OpenCL implementation tuned for the CPU can't beat a good OpenMP implementation. I dare say that no one has ever made OpenCL 2.0 code outside of Intel iGPUs. I think OpenCL will also prevent my code from running efficiently on any hardware that is not a graphics card today.. Because the favorable parallel computation done in OpenCL is well matched for GPU but quite inefficient on todays vanilla CPUs. OpenGL has stronger more performing implementations on some platforms (such as Open Source Linux drivers). The Apple GPU's heritage is from iOS devices, which never had OpenCL. Though to profit from such things you also need to be a bit more aware of the specific hardware your kernel will run on, but don't try to explicitly take those things into account using a shader (if even completely possible). Single-thread performance affects scenarios where CPU instructions have to be performed in a very specific order to obtain the desired result, such as physics simulations that calculate the trajectory of one ball after it's thrown. Compute in OpenGL lives to service the graphics pipeline. When you purchase through links on our site, we may earn an affiliate commission. But OpenGL GLSL 1.10 is still running on all macOS although deprecated the past decade. ;). Is "I didn't think it was serious" usually a good defence against "duty to rescue"? With OpenCL the whole point of "which typically handles computation only for computer graphics" is not given anymore. Try macOS 10.12.6, maybe you get better results. Note:The Vulkan API is most commonly used as a graphical backend in video games. Since then, he's gone back to journalism, enthusiastically reviewing the latest and greatest components for PC & Tech Authority, PC Powerplay and currently Australian Personal Computer magazine and PC Gamer. It's particularly important to AES encryption, which secures communication channels like the HTTPS protocol used by every major website since around 2016. . The executed kernel is customized on a range of different operational intensity values. This is the only thing I can think of that my be dropping the OpenCL score of the card in slot 1. Even though these tasks are vastly different than graphical workloads, they're still a good indication of how well the GPU runs graphical tasks like 3D rendering and video games. Curious how your GPU compares? A complete description of the individual Geekbench 4 CPU workloads can be found on the Geekbench website. Floating Point Floating point workloads measure floating point performance by performing a variety of processor-intensive tasks that make heavy use of floating-point operations. Is this possible with OpenCL? What is a usable OpenCL ideom for parallel random access like this? Profiling comes forfreewithcf4ocl (3)Simplify the analysis of the OpenCL environment and of kernel requirements, and (4) Allow for all levels of integration with existing OpenCL code: use as much or as few ofcf4ocl required for your project, with full access to the underlying OpenCL objects and functions at all times. OpenGL, in opposite, has strict division to CPU, which is task producer & GPU, which is task consumer. With OpenGL 4.3 and OpenGL ES 3.1 compute shaders, things become a bit more muddled. All software makes heavy use of integer instructions, meaning a high integer score indicates good overall performance. He enjoys covering the full breadth of PC tech; from business and semiconductor design to products approaching the edge of reason. I still have a hard time accepting that a single 5870 would actually deliver more performance, than a 295 and 280 working together, all with high utilization. These measurements are a good way to obtain comparable results among laptop models, helping you get a better idea of the kind of performance you can expect when running day-to-day tasks. This benchmark is similar in spirit, and based on, the STREAM benchmark for CPUs and supports OpenCL as well as many other APIs. Rasterization even enables some kind of random memory access (to "triangular connected" regions) with a guaranteed outcome (fragments overwritten ordered by z depth). As the OpenCL benchmark scales perfectly across all available GPUs, we found during beta testing that those with more GPUs ultimately ruled the leaderboard. On the other hand, random write access is not possible in any efficient manner (the only way to do is rendering triangles by texture driven vertex data). OpenGL 3.3, GLSL 1.5: How to setup a Texture Buffer Object containing various texture2D? :p). OpenCL existing requirement for full IEEE 754 floating point standard compliance 2 and its explicit memory model prevent OpenVX to be implemented only using OpenCL. Geekbench 6 scores are calibrated against a baseline score of 2500 (which is the score of an Intel Core i7-12700 performing the same task). Developing code for computation using OpenGL\GLSL will prevent you from using any hardware that is not a graphics card. Can you publish the code? We run the test three times, with two-minute idle intervals between each run, then note the average as our result. I know Nvidia Shaders do more work in 1 clock cycle than ATI. See the subsection descriptions above for a summary on what each subsection measures. Each workload type is described in further detail below. This is the reason why the dual-core, 4-thread Intel Core i3-10110U performs worse in online benchmarks compared to the quad-core, 4-thread AMD Ryzen 3 4300U. Find centralized, trusted content and collaborate around the technologies you use most. For example see Intels Knights Corner. We perform these tests one after another in a small, temperature-controlled room set to 22C (71.6F), with a tolerance of 0.5C. The "feature" that OpenCL is designed for general-purpose computation, while OpenGL is for graphics. OpenCL: A collection of OpenCL tests. The workloads are divided into three subsections: Crypto Crypto workloads measure the cryptographic instruction performance of your computer by performing tasks that make heavy use of crypto instructions. There must to be some global memory storage behind it. So, that's not exactly a stellar number for the Intel entry. Another point to mention (or to ask) is whether you are writing as a hobbyist (i.e. First, the publication shared no source link, and secondly, the benchmark purportedly came from Geekbench. Most modern applications are well-optimized for multiple threads, but if your laptop has good multi-thread performance, you'll also get a smoother experience when multitasking heavily or playing complex open-world video games. Nevertheless, the headline score of 44,638 in Geekbench's OpenCL tests is worthy of note, as the score beats the GeForce GTX 1650 Ti and is within earshot of the upcoming GeForce RTX 2050. A good example would be simulating the motion of a thousand stars around a black hole. You are using an out of date browser. We assign each multi-processor in the GPU to sweep a layered system. New York, Theintegerworkloads measure how quickly the CPU performs calculations with integer numbers; that is, whole numbers that don't involve any decimal points. Could a subterranean river or aquifer generate enough continuous momentum to power a waterwheel for the purpose of producing electricity? Sadly I can't share code. You might be surprised. It's not an indicator of gaming performance, nevertheless, it gives us a peek at what kind of compute performance the card has against its competitors. Is there any known 80-bit collision attack? OpenCL will remain for many years to come. Like CUDA and OpenCL are alternatives to one another, OpenGL is an alternative to systems like DirectX on Windows. This is actually a BIG win (saying that from a perspective of having thought through and implemented both variants). As or the screenshot, try opening it in paing and saving it again as jpeg:) Best CPU for gaming (opens in new tab): The top chips from Intel and AMD I must admit OpenCL has pretty good fixed function texture support which is one of the major OpenGL fixed function areas. Tom's Hardware is part of Future US Inc, an international media group and leading digital publisher. Sorry, just joking. OpenCL is a framework for heterogenous computing across different types of processors, including CPUs and GPUs. Chris' gaming experiences go back to the mid-nineties when he conned his parents into buying an 'educational PC' that was conveniently overpowered to play Doom and Tie Fighter. However, unlike software, there are no benchmarks for evaluating these compilers. While OpenCL returned a higher (faster) score on the M1 Max, there was essentially no difference in Cinebench scores: OpenCL scores were 37,795 (Pro) and 53,031 (Max). OpenGL 3.3 no texture gets rendered (black texture, C++, GLFW/SOIL). It's possible that the Intel 9600K processor used for the Arc result is causing a performance bottleneck. For example, OpenGL will automatically interpolate vertex data that has been declared with the. Geekbench detects which Compute API, if any, are supported on a device and provides Compute benchmarks for each of them. Best SSD for gaming (opens in new tab): Get into the game ahead of the rest. Most GPU programming is done on CUDA. While it is possible to compare scores across APIs (e.g., a OpenCL score with a Metal score) it is important to keep in mind that due to the nature of Compute APIs the performance difference can be due to more than differences in the underlying hardware (e.g., the GPU driver can have a huge impact on performance). Platform iOS That leaves more time and resources for driver debugging. OpenCL implements a "crunch arbitrary data into some other data" service.). 1) It is very important to have vectorized kernels. Geekbench 5 provides three different kinds of scores: Workload Scores Each time a workload is executed Geekbench calculates a score based on the computer's performance compared to the baseline performance. Okay, I had a little time today to run a fresh series of Geekbench tests in both Sierra and High Sierra. The numerical score doesn't mean anything in itself but is useful in comparisons. It'll launch applications, load webpages, and complete heavy tasks like renders and code compiles faster. I think this answer really needs more upvotes to show up earlier in this thread. You can do anything in GL (it is Turing-complete) but then you are driving in a nail using the handle of the screwdriver as a hammer. (optional), GB6 often does not complete the cpu bench, Geekbench 6 doesn't install correctly under Windows on Arm (on Ampere). While it is possible to compare scores across APIs (e.g., a OpenCL score with a Metal score) it is important to keep in mind that due to the nature of Compute APIs the performance difference can be due to more than differences in the underlying hardware (e.g., the GPU driver can have a huge impact on performance). However, as most Chromebooks only have integrated graphics, we expect this value to be in line with Windows devices using similar CPUs that don't have a dedicated graphics card. And well, I didn't come up with the idea to OpenCL in the first place - but as somebody else did, why shouln't it be put to its intended use? External Image, http://www.evga.com/forums/tm.aspx?high=≈mpage=1#89761, A 8800 GTS and a single 4850 produces around C453.4, A single XFX HD 5770 1GB produces around C1042.9, A single 295 produces around C1431 using both sides of the GPU, A single 295 and single 280 produce around C2575, "Setting different profiles for CPU and OpenCL does not mean anything so you got almost the same results (its hard to get the same results for CPU because of background tasks). We keep the laptop plugged in using its included adapter and ensure that the battery is at full charge before beginning our tests. So if floating-point accuracy is important to your calculations, OpenGL will not be the most effective way of computing what you need to compute. Not this much though - and the version of OpenCL on the Mac is still rather new and feature rich. The baseline score of 1,000 corresponds to the single-thread performance of an Intel Core i3-8100, an entry-level quad-core desktop CPU released in late 2017; because the score is designed to be linear, double the score means doubled performance, half the score means halved performance, and so on. One notable feature would be scattered writes, another would be the absence of "Windows 7 smartness". This graphics API is used in many games on iOS, as well as modern macOS games coded for Apple silicon. OpenCL is not a graphics API; it's a computation API. The score you get is simply the number of mega kernel loops (10^6) per second that your CPU can process (using 12 threads). Version v0.44 looked like this loaded up: First 1/2 of my 295 reporting 61% utilization, Second 1/2 of my 295 reporting 58% utilization, 280 checking in at a whopping 92% utilization (Go Dedicated PhysX processor!). OpenCL Score: 10441 Metal Score: 10840 MacBook Pro (15-inch Retina Mid 2015) Intel Core i7-4870HQ, 2.5Ghz 16GB DDR3 RAM, 1TB SSD liudayu macrumors member Nov 4, 2014 59 38 Sep 3, 2019 #8. Nvidia is more focused on General Purpose GPU Programming, AMD is more focused on gaming. Floating Point Floating point workloads measure floating point performance by performing a variety of processor-intensive tasks that make heavy use of floating-point operations. If not, OpenCL is more general and simpler to express compute problems. For example, parallel function evaluation can be done by rendering a to a texture using other textures. The original PolyBench Suite has been modified to run on GPUs and accelerators by using different programming languages, including OpenCL. ViennaCLBench is an OpenCL-based free open-source benchmark application with graphical user interface. 1 Answer. OpenCL Score 43189 System MacPro5,1 Intel Xeon X5690 3460 MHz (12 cores) Uploaded Sun, 30 Apr 2023 06:16:45 +0000. Hi Ben-Uri. Note:Our Geekbench benchmark determines the "cold performance" of the laptop. Version 0.3 added sequential copy. 565), Improving the copy in the close modal and post notices - 2023 edition, New blog post from our CEO Prashanth: Community is the future of AI. If we have missed something or you see anything that needs updating, please let us know by Contacting Us. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. We first saw the Nvidia GeForce MX570 officially confirmed towards the end of last year. LuxMark is a OpenCL cross-platform benchmark tool and has become, over past years, one of the most used (if not the most used) OpenCL benchmark. What is the symbol (which looks similar to an equals sign) called? GPUs have become increasingly prevalent in computation-heavy scenarios like animation rendering, so compute APIs like CUDA have been developed to increase the GPU's efficiency in these tasks. The OpenCL package has a nice test set that compares its own output against the reference project. A thorough description of the latest version, including in-depth performance evaluation for a larger number of OpenDwarfs, is described in OpenDwarfs: Characterization of Dwarf-based Benchmarks on Fixed and Reconfigurable Architectures by Krommydas, Feng, Antonopoulos, and Bellas in Journal of Signal Processing Systems (JSPS), Springer, October 2015. Cant't tell you without seeing your hardware configuration. One thought is to write your program in both and test them with respect to your priorities. The A770 is believed to be the flagship of Arc family. I wouldn't be surprised if the OpenCL implementation for Apple GPUs is merely just "functional" instead of "good". work_group_reduce The following operations are currently implemented: Dense matrix-matrix products (GEMM), Sparse matrix-vector products (SpMV with Matrix Market reader), Vector operations (AXPY) and Host-Device bandwidth (PCI-Express, etc.). OpenCL, a process which, with NVIDIA development tools, required minimal code changes in the kernel itself, as explained below. Also, OpenCL can run not just on GPUs, but also on CPUs and various dedicated accelerators. To make sure the results accurately reflect the average performance of each GPU, the chart only includes GPUs with at least five unique results in the Geekbench Browser. I don't know if it matters at all but my display is plugged into the card in slot 1. (aside: I suspect this is due to years of hardware and drivers being specifically tuned to graphics orientated workloads.). NY 10036. The Geekbench Compute Benchmark, developed by Primate Labs, measures the performance of GPUs performing common compute tasks, e.g. A system generally has good multi-thread performance if it has many threads and efficient task scheduling. The single-thread benchmark score is a weighted result of the CPU's performance while performing cryptographic, integer, and floating point workloads, using a single thread on one core. As a consumer with a limited budget, getting the most out of your laptop is a compromise between finding the laptop model that best suits your needs and its cost. CHO is an attempt at providing some sort of standard benchmark suite. ago Maybe I'm missing something? thanks! @wotanii: GLSL is the shading language used by OpenGL. Generally speaking, 690 to 719 is a good credit score on the commonly used 300-850 credit score range. However, we were warned that it would be in some way limited compared to RTX prefixed graphics chips. AMD Radeon Vega Frontier Edition LuxMark. (silly example) Fourier to Triangles and Quads? Likewise, better single-thread performance doesn't necessarily equate to better multi-thread performance if the CPU doesn't have many cores or threads. Copyright 2012 - 2022 IWOCL | All Rights Reserved |. Cinebench multi-core scores were 12,358 (Pro) and 12,377 (Max). GPGPU was cool for its time being, now just use OpenCL. The counting kernel loops thing has me wondering now :), Powered by Discourse, best viewed with JavaScript enabled. Score is up from C1786.0: This is a good OpenCL test to show off Multi-GPU Rigs. For example, different GPU drivers can have a huge impact on performance. According to theGeekbench 5 submission (opens in new tab), (via Benchleaks (opens in new tab) and Tom's Hardware (opens in new tab)), the card has 512 compute units, clocked at a maximum frequency of 2400MHz. Chrome OS:Unfortunately, the Android APK we use onChrome OSdoesn't support any GPU Compute tests. FYI - A good Multi-GPU OpenCL benchmark app, DirectCompute & OpenCL Benchmark. They have deprecated it; YES. Geekbench 4 uses several workloads to measure Compute performance. But you don't want to; not while there's a perfectly viable alternative. The following OpenCL benchmarks arecurrently available for public download. The scores for different APIs are comparable so getting C1000 and M10 means your graphic card can handle 100x more calculations per second than your CPU. If you want to know whether a laptop can process photo edits, run physics simulations, or compile code quickly enough to suit your needs, you can look to a Geekbench benchmark. Another thing we have spotted is that the 'GeForce MX570 A' will be a variant released lacking NVENC/NVDEC support. The GPUs have fixed modules (like 'Render Output Units' and 'Texture Mapping Units') expressed in OpenGL features. The ergonomic design of the machine means it does slip into your hand . @dronus Well, yes it ignores the fixed-function parts. Visit our corporate site (opens in new tab). Apple's own software still also includes a fair amount of OpenCL implementations. API OpenCL OpenCL Score 1068 System iPad Air (5th generation) Apple M1 3190 MHz (8 cores) Uploaded Apr 17, 2023 Platform iOS API Metal Metal Score 32434 System ASUSTeK COMPUTER INC. ROG Strix G634JY_G634JY Intel Core i9-13980HX 2200 MHz (24 cores) Uploaded Apr 17, 2023 Platform Windows API OpenCL OpenCL Score 196703 For example, if you're rendering to a floating-point framebuffer, the driver might just decide to give you an R11_G11_B10 framebuffer, because it detects that you aren't doing anything with the alpha and your algorithm could tolerate the lower precision. You must log in or register to reply here. The Geekbench score provides a way to quickly compare performance across different computers and different platforms without getting bogged down in details. The A770 returns an OpenCL score of 85585. OpenCL which requires only simple thing like driver, amdgpu-pro, shipped with all nesesary libs (i did OpenCL miner firmware with only 50mb footprint). It provides a consistent workload to the device, and generates a Geekbench score by evaluating the amount of work that it is able to do while the battery is discharging and the amount of time it takes for the battery to discharge. 1) You can create a program scope variable if you use OpenCL 2.0 implementation: void increase (volatile __global int* counter) { atomic_inc (counter); } __global int counter = 0; __kernel void test () { volatile __global int . On the flip-side, a CPU with many cores, which individually run tasks more slowly, will very likely not provide any extra benefits to running a few light productivity workloads at a time. Also, OpenGL compute shaders require 4.x-capable hardware, while OpenCL can run on much more inferior hardware. The battery benchmark can also be run in Partial Discharge mode, for 3 hours. Chris still puts far too many hours into Borderlands 3, always striving to become a more efficient killer. When you do scientific computing using OpenGL you always have to think about how to map your computing problem to the graphics context (i.e. SwitchArcade Round-Up: Reviews Featuring Advance Wars 1+2 Re-Boot Camp, Plus New Releases and More, Best iPhone Game Updates: Plants vs Zombies 2, Bacon The Game, Star Traders: Frontiers, and More, Marvel Snap Rocks Out to the Greatest Hits of the Guardians of the Galaxy in the Latest Season, Horror Mystery-Adventure Paranormasight: The Seven Mysteries of Honjo Is Discounted for a Limited Time Alongside Other Square Enix Games, SwitchArcade Round-Up: Nuclear Blaze, Varney Lake, Fran Bow, Plus Todays Other Releases and Sales, Voice of Cards: The Forsaken Maiden Review A Good Starting Point, Vampire Survivors Being Adapted Into Premium Animated TV Series by Story Kitchen and Poncle. Apple continues to deprecate OpenCL as they try and push developers to Metal (2) so I would not be surprised if the Windows score was significantly higher. Thinking in kernels and memory streams, the emulation of such behaviour would mean random access with well defined ordered mutexes among all parallel threads or something else. You are right about GL state being rather heavy but well written GL code can mostly avoid state changes, especially for compute-like tasks (Vulkan is way better in this respect btw). Higher scores are better, with double the score indicating double the performance. Geekbench currently supports the following Compute APIs: OpenCL, CUDA, Metal, and RenderScript. Ingenious Counter-Strike players are exploiting Steam's new notes function to score noscopes, Star Wars Jedi: Survivor Steam reviews hit 'mostly negative' as players slam performance issues'F*** us PC gamers right? ", Question: If scores for both CPUs and GPUs are generated by counting mega kernel loops (10^6) per second. Connect and share knowledge within a single location that is structured and easy to search. My advice would be that if your compute program feels like it maps nicely to the graphics domain then use OpenGL. platforms you do not need a window (and its context binding) to do calculations. New improved version 0.45, with better workload balancing. My specific experience of this has been doing image filter (gather) kernels across AMD, nVidia, IMG and Qualcomm GPUs. By the time Apple GPUs come to the Mac, OpenCL is already a deprecated API. The memory is reported at 12.7GB, but that could be a reporting error. Making statements based on opinion; back them up with references or personal experience. We are hesitant to compare different vendor architecture GPUs using OpenCL scores, but we have put together a small selection of GeForce OpenCL scores with the MX570 mid-table below. Thanks for contributing an answer to Stack Overflow! Something that hasn't been mentioned in any answers so far has been speed of execution. Remember that the MX570 graphics processor isn't meant to be a stand-out performer, but rather bring Ampere technologies, lower-power efficient CUDA Cores, and GDDR6 to Nvidia Optimus laptops for balanced battery life and performance. Best graphics card (opens in new tab): Your perfect pixel-pusher awaits It focuses on common linear algebra operations on multi-core CPUs, GPUs, and MIC from major vendors. That means two languages to learn, two APIs to figure out. Scores 720 and above are considered excellent, while scores 630 to 689 are considered fair . In both cases you're always trying to map your math operations to hardware with the highest performance possible. Each Compute workload has an implementation for each supported Compute API. Depending on the operating system and manufacturer, some tests may not be available; scroll down to each individual test to see the details. The only reason to pick OpenGL for any kind of non-rendering compute operation is to support hardware that can't run OpenCL. With textures of different scale its also easy to map a different amount (ususally 2^n) of values onto another. For more information, see our Performance Over Time test article. The card managed to pass the OpenCL test benchmarks with a score of 169779 points. Very light CPU utilization, showing only 2%. If you need to run more demanding workloads like games or video editing, or you multitask more often, you'll have a much smoother experience with a quad-core CPU, whether or not it can run multiple threads per core. Generally speaking, the higher the Geekbench score, the faster the laptop feels overall. I'm pretty sure it isn't doing 8x the amount of work. BabelStream is a benchmark used to measure the memory transfer rates to/from capacity memory. work_group_broadcast: The data on this chart is calculated from Geekbench 6 results users have uploaded to the Geekbench Browser. Software working with large data structures (e.g., digital content creation) or with referential data structures (e.g., databases, web browsers) rely on good memory performance to keep the processor busy. Version 0.2 tests sequential write and read speeds. There are parts of GPU hardware which vanilla CL won't use but that won't keep a separate extension from doing so. Integer Integer workloads measure the integer instruction performance of your computer by performing processor-intensive tasks that make heavy use of integer instructions. if your task only is to compute and you have no running x server, and, even, no monitor attached. Individual operations tend to be about the same between GL/CL but the GLSL compilers seem more mature and produce overall tighter code. No more CPU, GPU (etc) notions are longer needed - you have just Host & Device(s). The implementation has no option to decide something else later. A lot of the above are mostly for better CPU - GPU interaction: Events, Shared Virtual Memory, Pointers (although these could potentially benefit other stuff too). OpenGL is just more narrow-scope instrument. However, OpenCL can be used to efficiently implement a user node to run on a GPU (see Chapter 13 for more information). Some CPUs can run multiple threads on a single physical core, which improves multi-thread performance. . The OpenGL implementations invariably run faster even after hardcore OpenCL kernel optimization. You can use OpenGL to do arbitrary computations. For a better experience, please enable JavaScript in your browser before proceeding. macOS:We use the Metal API. Some of these tests used by Geekbench include edge-finding algorithms, automatic contrast adjustment of an image, face detection, and fluid/particle simulations. Well as of OpenGL 4.5 these are the features OpenCL 2.0 has that OpenGL 4.5 Doesn't (as far as I could tell) (this does not cover the features that OpenGL has that OpenCL doesn't): Workgroup Functions: The benchmark supportsfournative GPGPU/APU platforms including OpenCL 2.0+. So how could OpenGL work under CL? A processor with multithreading technology performs better than a processor with the same amount of cores without the capability; however, it performs worse than a processor with the same number of physical cores as the CPU with multiple threads per core. But what else would you expect than using more than a dozen parallel "CPUs" without breaking your head about how to translate - e.g.
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