It’s dangerous to go outside right now, but with a drone, you are free to explore the outside world without the risk of contracting coronavirus. This drone features a high-quality quad HD camera and it comes bundled with tons of extra accessories including a 64GB SD card, a cleaning kit, and a bag for carrying and storing the drone and equipment in. Right now you can get it from Adorama marked down from $796.29 to just $524.00.
DJI designed this quadcopter with a 12mp camera that’s capable of capture high quality, 180-degree 32MP panorama photos. The drone is able to fly for up to 21 minutes on a single charge as well, giving you plenty of time to explore before the battery runs dry. You can get one of these drones now from Best Buy marked down from $1,149.99 to just $699.99.
You can now pre-order DJI’s Mavic Air 2 drone, which is able to fly at a fast speed of 68kph. It also has a maximum flight time of 34 minutes. This drone is set with a price of $988.00 and can be pre-ordered from Adorama.
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Back in the old days last century, if you wanted to hit the top of the charts, you grabbed a guitar, talked one of your friends into trying to play drums, started a band and launched into performing. It was an inexact science, certainly, but it was perhaps the most tried-and-true method for new music talent to get noticed for a solid five decades.
But just like everything else, the world of pop stardom has changed. New artists don’t play instruments or start bands anymore to make their bones. They hole up in the studio/bedroom, hone their music to a fine point on production-quality home equipment, then unleash it to an often shocked world over the web.
Home recording technology has changed everything in music over the past 20 years — and if you want to join the revolution, it’s time to study up. With the training in The Complete EDM Production Bundle: Learn to DJ ($19.99, over 90 percent off), you can acquire the skills needed to make a mark in the new music order.
The seven-course collection packing in more than 26 hours of training is broken up into three distinct categories: technical basics, music creation, and live performance.
Music newbies can get started with Introduction to Electronic Music, Electronic Music Primer, and Music Producer Masterclass: Make Electronic Music, three courses dedicated to laying the foundations of creating EDM tracks. From the fundamentals of audio signal processing and recording to the top-level tricks employed by music production experts, students will get an idea of what it takes to launch a music career in 2020.
Of course, technical achievement doesn’t mean much if you don’t have the right music, which is why the second phase of courses in this bundle — Music Theory for Electronic Musicians, Music Theory for Electronic Musicians 2: Minor Keys and More, and Music Theory For Electronic Musicians 3: Extended Harmony — actually dig into the nitty-gritty of what makes popular music. Students here learn how to create on a DAW (digital audio workstation), analyze tracks by artists like Skrillex, Daft Punk, and Avicii to understand why their hits became hits, then produce nine tracks using different techniques to highlight the learning.
Finally, The Live Performance Master Class for Electronic Musicians explains the ins and outs of live EDM performing.
Hong Kong was one of the early epicenters of the coronavirus pandemic, and public health officials are only beginning to get a handle on the situation. A new type of disinfectant could help bring down COVID-19 infections, and combat future diseases. Researchers from the Hong Kong University of Science and Technology (HKUST) have developed a disinfectant that can protect surfaces for up to 90 days.
Currently, public health officials recommend using substances like bleach to clean surfaces. That will kill the SARS-CoV-2 virus and most other microorganisms. However, the protection is short-lived. The antimicrobial properties of traditional disinfectants decline rapidly as the substances evaporate. As soon as someone touches that surface again, it’s a potential vector for disease transmission. The new “MAP-1” disinfectant from HKUST addresses that by holding its sterilizing payload in reserve for when it’s really needed.
MAP-1 is a spray that coats and evaporates on surfaces, but it’s much more advanced than bleach or alcohol. The spray carries millions of polymer nanocapsules that adhere to surfaces and remain there after the carrier liquid has dried. These non-toxic capsules contain a disinfectant that remains in suspension until touched. The heat from a hand or moisture activates the capsules, releasing disinfectant onto the surface. It’s not only effective on coronavirus, but also on other viruses like measles and rubella and potentially dangerous bacteria.
The longevity of MAP-1 will vary based on how often someone touches it, but HKUST says it can last for up to 90 days. The nanocapsules can adhere to hard surfaces like door handles, countertops, and handrails, but it also works on soft materials like fabric, plastic, and more. Following testing by HKUST, a company called Germagic has signed on to manufacture and distribute MAP-1, which it has confusingly branded as “Germagic Thyme.”
The nanofiber material that makes up the wall of the nanocapsules.
Germagic has already applied the material to more than one-thousand low-income homes in Hong Kong. These homes usually have many residents living close together, which makes disease transmission a greater threat. Coating large public areas like schools might cost a few thousand dollars, but that’s not dramatically more than it costs to deep-clean these facilities with traditional disinfectants multiple times per day, as many health officials recommend. Germagic will begin selling MAP-1 directly to consumers in 50-200ml bottles soon. The company says those will cost between $9 and $32.
OpenCL, once lauded as the future of GPGPU computing, has more recently faded out of the spotlight. Most of the PC companies that supported it have found reasons to pursue other goals: Apple has its own Metal API, Nvidia has the phenomenally successful and self-created CUDA, and AMD has been focused on Linux and its RoCm solution. Intel seems to be the only company working on its OpenCL drivers and support on a consistent basis.
Even so, the OpenCL 2.2 standard, which was published in 2017, isn’t yet supported by any vendor in the entire computing industry. It’s not a good sign when you can’t find a single company to support your standard three years after you publish it, and the Khronos Group is taking a radical approach to OpenCL 3.0 development. Specifically, they’re junking OpenCL 2.0 and going back to a fork of OCL 1.2 development.
To be clear, OCL 2.x code and capability won’t be stripped out of the standard, it’ll simply become an optional way to support OCL hardware. All features introduced up to OpenCL 2.2 will remain available for any vendor that wants to write a driver to support them. The reason the new standard is based on OpenCL 1.2 is that this is the last version that everyone agrees contains absolutely necessary functions required to support the full sweep of use-cases for the standard. The agreement is important in this case because Khronos is a consortium comprised of various member organizations, but it doesn’t wield any power of its own.
Other than the core OCL 1.2 capabilities, everything introduced to the standard in OCL 2.x and 3.0 will be optional. Each vendor will be able to support specific capabilities that make sense for their hardware, but there are no “one size fits all” restrictions of the sort that led vendors to walk away from the standard in the first place. This new approach is modeled on the way Khronos rolled out Vulkan, and OCL 3.0 will be easy for developers to support. All OpenCL 1.2 apps will run perfectly on an OpenCL 3.0 device and OpenCL 2.x applications will run perfectly on OCL 3.0 devices so long as those devices support the features the app is using. If you have an OCL 1.2 or 2.x app, you don’t have to worry about OCL 3.0 impacting your backward compatibility.
Those of you who were hoping to see OpenCL C++ catch on, though… we have bad news. The language is being junked entirely. It will be replaced by “C++ for OpenCL,” which is similar to OpenCL C++, but distinct from it and run under the auspices of a different project.
The big new feature of the standard is Asynchronous DMA support, which allows DMA transactions to run at the same time as compute kernels or synchronously with other DMA transactions.
Anandtech has more details on the low-level features and capabilities being added to the standard if you want to read up on the topic. It’s not clear that this new version of OpenCL will make any real difference for the PC industry, especially for Windows users. Despite the fact that applications like Folding@Home and Blender use OpenCL for various purposes (Blender uses it for Cycles rendering on AMD GPUs, for example), none of the major vendors seem to be making the language front and center to their future plans, though this could change once Intel launches the datacenter version of Xe.
Ever since 3dfx debuted the original Voodoo accelerator, no single piece of equipment in a PC has had as much of an impact on whether your machine could game as the humble graphics card. While other components absolutely matter, a top-end PC with 32GB of RAM, a $4,000 CPU, and PCIe-based storage will choke and die if asked to run modern AAA titles on a ten-year-old card at modern resolutions and detail levels. Graphics cards, aka GPUs (Graphics Processing Units) are critical to game performance and we cover them extensively. But we don’t often dive into what makes a GPU tick and how the cards function.
By necessity, this will be a high-level overview of GPU functionality and cover information common to AMD, Nvidia, and Intel’s integrated GPUs, as well as any discrete cards Intel might build in the future based on the Xe architecture. It should also be common to the mobile GPUs built by Apple, Imagination Technologies, Qualcomm, ARM, and other vendors.
Why Don’t We Run Rendering With CPUs?
The first point I want to address is why we don’t use CPUs for rendering workloads in gaming in the first place. The honest answer to this question is that you can run rendering workloads directly on a CPU. Early 3D games that predate the widespread availability of graphics cards, like Ultima Underworld, ran entirely on the CPU. UU is a useful reference case for multiple reasons — it had a more advanced rendering engine than games like Doom, with full support for looking up and down, as well as then-advanced features like texture mapping. But this kind of support came at a heavy price — many people lacked a PC that could actually run the game.
In the early days of 3D gaming, many titles like Half-Life and Quake II featured a software renderer to allow players without 3D accelerators to play the title. But the reason we dropped this option from modern titles is simple: CPUs are designed to be general-purpose microprocessors, which is another way of saying they lack the specialized hardware and capabilities that GPUs offer. A modern CPU could easily handle titles that tended to stutter when running in software 18 years ago, but no CPU on Earth could easily handle a modern AAA game from today if run in that mode. Not, at least, without some drastic changes to the scene, resolution, and various visual effects.
As a fun example of this: The Threadripper 3990X is capable of running Crysis in software mode, albeit not all that well.
What’s a GPU?
A GPU is a device with a set of specific hardware capabilities that are intended to map well to the way that various 3D engines execute their code, including geometry setup and execution, texture mapping, memory access, and shaders. There’s a relationship between the way 3D engines function and the way GPU designers build hardware. Some of you may remember that AMD’s HD 5000 family used a VLIW5 architecture, while certain high-end GPUs in the HD 6000 family used a VLIW4 architecture. With GCN, AMD changed its approach to parallelism, in the name of extracting more useful performance per clock cycle.
Nvidia first coined the term “GPU” with the launch of the original GeForce 256 and its support for performing hardware transform and lighting calculations on the GPU (this corresponded, roughly to the launch of Microsoft’s DirectX 7). Integrating specialized capabilities directly into hardware was a hallmark of early GPU technology. Many of those specialized technologies are still employed (in very different forms). It’s more power-efficient and faster to have dedicated resources on-chip for handling specific types of workloads than it is to attempt to handle all of the work in a single array of programmable cores.
There are a number of differences between GPU and CPU cores, but at a high level, you can think about them like this. CPUs are typically designed to execute single-threaded code as quickly and efficiently as possible. Features like SMT / Hyper-Threading improve on this, but we scale multi-threaded performance by stacking more high-efficiency single-threaded cores side-by-side. AMD’s 64-core / 128-thread Epyc CPUs are the largest you can buy today. To put that in perspective, the lowest-end Pascal GPU from Nvidia has 384 cores, while the highest core-count x86 CPU on the market tops out at 64. A “core” in GPU parlance is a much smaller processor.
Note: You cannot compare or estimate relative gaming performance between AMD, Nvidia, and Intel simply by comparing the number of GPU cores. Within the same GPU family (for example, Nvidia’s GeForce GTX 10 series, or AMD’s RX 4xx or 5xx family), a higher GPU core count means that GPU is more powerful than a lower-end card. Comparisons based on FLOPS are suspect for reasons discussed here.
The reason you can’t draw immediate conclusions on GPU performance between manufacturers or core families based solely on core counts is that different architectures are more and less efficient. Unlike CPUs, GPUs are designed to work in parallel. Both AMD and Nvidia structure their cards into blocks of computing resources. Nvidia calls these blocks an SM (Streaming Multiprocessor), while AMD refers to them as a Compute Unit.
A Pascal Streaming Multiprocessor (SM).
Each block contains a group of cores, a scheduler, a register file, instruction cache, texture and L1 cache, and texture mapping units. The SM / CU can be thought of as the smallest functional block of the GPU. It doesn’t contain literally everything — video decode engines, render outputs required for actually drawing an image on-screen, and the memory interfaces used to communicate with onboard VRAM are all outside its purview — but when AMD refers to an APU as having 8 or 11 Vega Compute Units, this is the (equivalent) block of silicon they’re talking about. And if you look at a block diagram of a GPU, any GPU, you’ll notice that it’s the SM/CU that’s duplicated a dozen or more times in the image.
And here’s Pascal, full-fat edition.
The higher the number of SM/CU units in a GPU, the more work it can perform in parallel per clock cycle. Rendering is a type of problem that’s sometimes referred to as “embarrassingly parallel,” meaning it has the potential to scale upwards extremely well as core counts increase.
When we discuss GPU designs, we often use a format that looks something like this: 4096:160:64. The GPU core count is the first number. The larger it is, the faster the GPU, provided we’re comparing within the same family (GTX 970 versus GTX 980 versus GTX 980 Ti, RX 560 versus RX 580, and so on).
Texture Mapping and Render Outputs
There are two other major components of a GPU: texture mapping units and render outputs. The number of texture mapping units in a design dictates its maximum texel output and how quickly it can address and map textures on to objects. Early 3D games used very little texturing because the job of drawing 3D polygonal shapes was difficult enough. Textures aren’t actually required for 3D gaming, though the list of games that don’t use them in the modern age is extremely small.
The number of texture mapping units in a GPU is signified by the second figure in the 4096:160:64 metric. AMD, Nvidia, and Intel typically shift these numbers equivalently as they scale a GPU family up and down. In other words, you won’t really find a scenario where one GPU has a 4096:160:64 configuration while a GPU above or below it in the stack is a 4096:320:64 configuration. Texture mapping can absolutely be a bottleneck in games, but the next-highest GPU in the product stack will typically offer at least more GPU cores and texture mapping units (whether higher-end cards have more ROPs depends on the GPU family and the card configuration).
Render outputs (also sometimes called raster operations pipelines) are where the GPU’s output is assembled into an image for display on a monitor or television. The number of render outputs multiplied by the clock speed of the GPU controls the pixel fill rate. A higher number of ROPs means that more pixels can be output simultaneously. ROPs also handle antialiasing, and enabling AA — especially supersampled AA — can result in a game that’s fill-rate limited.
Memory Bandwidth, Memory Capacity
The last components we’ll discuss are memory bandwidth and memory capacity. Memory bandwidth refers to how much data can be copied to and from the GPU’s dedicated VRAM buffer per second. Many advanced visual effects (and higher resolutions more generally) require more memory bandwidth to run at reasonable frame rates because they increase the total amount of data being copied into and out of the GPU core.
In some cases, a lack of memory bandwidth can be a substantial bottleneck for a GPU. AMD’s APUs like the Ryzen 5 3400G are heavily bandwidth-limited, which means increasing your DDR4 clock rate can have a substantial impact on overall performance. The choice of game engine can also have a substantial impact on how much memory bandwidth a GPU needs to avoid this problem, as can a game’s target resolution.
The total amount of on-board memory is another critical factor in GPUs. If the amount of VRAM needed to run at a given detail level or resolution exceeds available resources, the game will often still run, but it’ll have to use the CPU’s main memory for storing additional texture data — and it takes the GPU vastly longer to pull data out of DRAM as opposed to its onboard pool of dedicated VRAM. This leads to massive stuttering as the game staggers between pulling data from a quick pool of local memory and general system RAM.
One thing to be aware of is that GPU manufacturers will sometimes equip a low-end or midrange card with more VRAM than is otherwise standard as a way to charge a bit more for the product. We can’t make an absolute prediction as to whether this makes the GPU more attractive because honestly, the results vary depending on the GPU in question. What we can tell you is that in many cases, it isn’t worth paying more for a card if the only difference is a larger RAM buffer. As a rule of thumb, lower-end GPUs tend to run into other bottlenecks before they’re choked by limited available memory. When in doubt, check reviews of the card and look for comparisons of whether a 2GB version is outperformed by the 4GB flavor or whatever the relevant amount of RAM would be. More often than not, assuming all else is equal between the two solutions, you’ll find the higher RAM loadout not worth paying for.
Check out our ExtremeTech Explains series for more in-depth coverage of today’s hottest tech topics.
AT&T, Comcast, and Verizon all announced extensions of some of the coronavirus policies they’ve enacted to-date, extending those guarantees out to June 30. The responses from each company are somewhat unique, so we’ll cover each below:
Comcast
Comcast will waive late fees if you contact them and tell them you cannot pay. It has pledged not to disconnect any Xfinity internet, mobile, or voice user, and it’s making Xfinity WiFi hot spots available for free across the United States.
All Comcast data caps have been waived through June 30 as well. If you do not have home internet but can receive a Comcast hookup, the company is offering 60 days of complimentary service for all new customers through June 30. The service typically costs $6.95 per month.
Verizon
Verizon will not terminate residential or small business service nor charge late fees on any customer, provided you notify them of your hardship. Last week the company announced it would give wireless customers an extra 15GB of data in May.
AT&T
AT&T has announced its own initiatives, and they largely mirror what Comcast and Verizon are doing. Once again, if you notify the company, it will waive all late fees and overage charges associated with wired or wireless usage.
The various bits of information in the coronavirus updates from AT&T, Verizon, and Comcast are all a little funnier if you think about them as attempts to respond to the pandemic. Verizon, for example, wants us to know it’ll be increasing its capital expenditures later this year. Don’t mistake me — that’s an important statement regarding future spending in a deeply uncertain time — but it’s also a little funny to think about a company saying: “We know there’s a deadly disease killing people, but we promise to keep investing.”
Does Anybody Think Wireline Data Caps Are Remotely Justifiable Now?
One thing that’s been common knowledge in the IT industry is that wireline data caps, like those of which Comcast imposes, are literally nothing but a way for companies to overcharge customers for service. It’s been admitted by engineers, industry CEOs, and leaked documents, none of which go to any trouble to hide this fact. Even as the cost of delivering traffic to you has cratered, ISPs have continued to charge overage fees for data caps that have no technical reason to exist, year after year. A huge percentage of workers in the United States have been sheltering in place for months. Network usage has surged. Bandwidth demands have grown significantly. The internet may have struggled for a few days, but the network has stood firm.
There was never an objective reason for Comcast and other companies to enforce bandwidth caps, beyond that they were legally allowed to fleece customers for additional overage fees and decided to do so. Now that they’re gone, they’ve got no business coming back.
A new paper suggests that there may be 19 asteroids — all part of the Centaur family — that didn’t come from our own solar system at all. If this were proven true, it would mean we have ancient material formed around an alien star in orbit in our own solar system.
Centaurs are some of the most interesting space rocks in our solar system. A Centaur is formally defined as a small body that orbits between Jupiter and Neptune, and that crosses the orbit of at least one giant planet. They sit outside the range of the Jupiter trojans but are much closer to the sun than either the scattered disc or Kuiper Belt. The fact that they cross the orbit of at least one giant planet means that Centaurs do not have stable orbits beyond a time scale of a few million years.
Centaur orbits, as compared to the outer planets, Kuiper Belt objects, and the scattered disc. Image by Wikipedia, CC BY-SA 3.0
Centaurs are called such because they demonstrate the characteristics of both asteroids and comets. The first Centaur discovered, 2060 Chiron, was found in 1977. Initially, it brightened by 75 percent and developed a cometary coma, with a tail detected in 1993. But Chiron is approximately 220km in diameter, much larger than a typical comet nucleus, and it may have a ring system — something never observed around a comet. What do you call a half-comet, half-asteroid? A comeroid Centaur, obviously.
The fact that a Centaur’s orbit around the sun isn’t stable is one of their defining characteristics, which is where this new paper comes in. According to the researchers, there are 19 Centaurs whose orbits and inclination within our solar system can only be explained if they did not originate here at all. Objects in unstable orbits around the sun follow one of three outcomes: They assume stable orbits around either a planet or our sun, they fall into the gravity well of either a planet or the sun, or they are ejected back into the interstellar medium.
Prior to this study, only one potential extra-solar Centaur had been identified, 514107 Kaʻepaokaʻawela. The idea that there might be 19 such objects out of a total population of between 44,000 – >10M is not crazy, nor is the idea that our solar system might have captured such asteroids in the relatively recent past. We have recently detected two comets with an interstellar origin — comet Borisov and the cigar-shaped ‘Oumuamua.
The authors, Namouni and Morais, analyzed the orbits of Centaurs with particularly tilted orbits relative to the plane of the ecliptic (the plane in which the major planets and asteroids all move). They found 19 objects whose orbits cannot be explained if they began life as objects that formed within our solar system. If they’re captured space rocks, on the other hand, their orbits are perfectly explainable. It is not clear that all 19 objects are from the same ejection event, either.
Namouni and Morais do not claim that their gravitational interaction simulation proves that Centaurs are extrasolar captures. But if they are, it would mean there are pieces of another solar system caught within our own. Such material might date back to the Sun’s formation (if it was captured near the beginning of our solar system) or it could have been captured within the past few million years. The dinosaurs, for all their many accomplishments, were absolutely terrible at leaving astronomical records.
Again, there’s precedent for this kind of theory. We have already located two “stellar siblings” of Sol — HD 162826 (110 LY distant, F8V star, 4.5B years old) and HD 186302 (184 LY distant, G2V star, 4.57B years old). Our sun is a G2V star thought to have ignited some 4.6B years ago. It’s clear that there was a great deal of exchange going on at that point in time; the protoplanetary disk of the solar system was clearly seeded with heavy metals by a supernova that went off nearby while our planets were just forming. The explosion wasn’t close enough to scatter our disc, but it left a telltale signature we can still pick up.
The coolest thing about these findings is that it means we could gather information from asteroids that didn’t originate here. It doesn’t really matter if they represent a 4.5B-year-old capture from a long-lost stellar sibling or if these Centaurs are random space rocks like Borisov or ‘Oumuamua. No matter where they came from or how long ago we formed, we’d learn a tremendous amount about conditions elsewhere in the galaxy — and we could learn them in a matter of a few decades, rather than the tens of thousands of years currently required to send an unmanned probe to another solar system.
That’s an excellent reason to focus some probes on these Centaurs. Any time there’s a chance of gathering information in decades that would otherwise take tens of thousands of years, it’s worth exploring.
