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Western heat wave threatens health in vulnerable communities

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PHOENIX — Extreme temperatures like the ones blistering the American West this week aren’t just annoying, they’re deadly.

People — along with plants and animals — need cooler temperatures at night to recover from the stress of high heat, scientists and doctors said. But with overnight temperatures in the 90s, that’s not happening.

Karuppana noted that many people she sees may have no car and have to take public transportation in the Phoenix heat, walking through neighborhoods with few trees and waiting at bus and light rail stops with no or little shade. Some people live in poorly ventilated mobile homes or without air conditioning. Or they may work outside in the sun as construction workers or landscapers.

Phoenix has been baking in temperatures above 115 degrees (46 Celsius) all week. The high Friday hit a record 117 degrees (47 Celsius) after breaking another Thursday at 118 degrees (48 Celsius). Daily records also were set this week in places across the U.S. West, such as Nevada and California, including 128 degrees (53 Celsius) in Death Valley on Thursday.

Those who are vulnerable to high temperatures include the very young, the very old and people with heart or kidney disease, ailments that disproportionately affect communities of color.

“We are activated for Phoenix and monitoring it closely,” said Nicolette Louissaint, executive director of the Washington nonprofit Healthcare Ready, which was founded after Hurricane Katrina to help communities deal with natural disasters.

Louissaint said her organization has helped in heat emergencies by funding cooling centers that offer bottled water and shade or arrange transportation for older people without cars who need dialysis or heart checkups.

“Extreme heat really exacerbates those kind of serious medical conditions,” she said. “It’s tough on people who don’t have a lot of money.”

Phoenix and other local governments around the Southwest remind people on social media to drink lots of water, stay out of the sun if possible and take frequent breaks on hot days. They warn people to not leave children or pets in vehicles, and they work with nonprofits like the Salvation Army to open facilities that allow people to cool off.

The rising risks of the heat became painfully clear three years ago when 72-year-old Stephanie Pullman died at her Phoenix-area home after Arizona’s largest electric utility turned off her service for failure to pay $51. A coroner listed “environmental heat exposure” as one of the causes of her 2018 death.

It led to a series of moratoriums on overdue electrical bills in Arizona that continued through the end of last year amid the coronavirus pandemic. The utility, Arizona Public Service, says it has suspended service disconnections and waived late fees through Oct. 15.

The county that includes Phoenix has reported three heat-related deaths as of Saturday, with an additional 20 fatalities being investigated as possibly caused by high temperatures.

Heat-related deaths in Maricopa County have been rising dramatically in recent years, with 323 reported last year, the highest ever recorded. The highest rates were reported among Black people and Native Americans. About 80% of those who died were men.

People living on the street are especially at risk. The Maricopa County medical examiner has said heat was a primary or secondary cause in the death of 146 homeless people last year, when the summer was the hottest ever recorded in Phoenix.

Scientists say the number of heat deaths in the U.S. West and the world over were only expected to rise.

As average temperatures rise worldwide, heat is becoming more extreme, said Gerald Meehl, senior scientist with the National Center for Atmospheric Research in Boulder, Colorado.

“As the average climate warms up from increasing human-produced greenhouse gases, we are seeing more intense, more frequent and longer lasting heat waves,” Meehl said.

A study last month estimated the number of heat deaths each year that can be attributed to human-caused global warming. It included about 200 U.S. cities and found more than 1,100 deaths a year from climate change-caused heat, many of them in the East and Midwest, where many people don’t have air conditioning or are not acclimated to hot weather.

Joellen Russell, climate science professor at the University of Arizona in Tucson, said the Southwest is an early example of what will hit the rest of the nation later when it comes to the dangers of heat extremes caused by global warming.

“I think we’d better hurry up,” she said. “Our kids are counting on us.”

———

Associated Press Science Writer Seth Borenstein contributed from Washington. Follow Snow on Twitter at https://twitter.com/asnowreports and Borenstein at https://twitter.com/borenbears.


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OpenAI releases Triton, a programming language for AI workload optimization

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All the sessions from Transform 2021 are available on-demand now. Watch now.


OpenAI today released Triton, an open source, Python-like programming language that enables researchers to write highly efficient GPU code for AI workloads. Triton makes it possible to reach peak hardware performance with relatively little effort, OpenAI claims, producing code on par with what an expert could achieve in as few as 25 lines.

Deep neural networks have emerged as an important type of AI model, capable of achieving state-of-the-art performance across natural language processing, computer vision, and other domains. The strength of these models lies in their hierarchical structure, which generates a large amount of highly parallelizable work well-suited for multicore hardware like GPUs. Frameworks for general-purpose GPU computing such as CUDA and OpenCL have made the development of high-performance programs easier in recent years. Yet, GPUs remain especially challenging to optimize, in part because their architectures rapidly evolve.

Domain-specific languages and compilers have emerged to address the problem, but these systems tend to be less flexible and slower than the best handwritten compute kernels available in libraries like cuBLAS, cuDNN or TensorRT. Reasoning about all these factors can be challenging even for seasoned programmers. The purpose of Triton, then, is to automate these optimizations, so that developers can focus on the high-level logic of their code.

“Novel research ideas in the field of deep learning are generally implemented using a combination of native framework operators … [W]riting specialized GPU kernels [can improve performance,] but [is often] surprisingly difficult due to the many intricacies of GPU programming. And although a variety of systems have recently emerged to make this process easier, we have found them to be either too verbose, lack flexibility, generate code noticeably slower than our hand-tuned baselines,” Philippe Tillet, Triton’s original creator, who now works at OpenAI as a member of the technical staff, wrote in a blog post. “Our researchers have already used [Triton] to produce kernels that are up to 2 times more efficient than equivalent Torch implementations, and we’re excited to work with the community to make GPU programming more accessible to everyone.”

Simplifying code

According to OpenAI, Triton — which has its origins in a 2019 paper submitted to the International Workshop on Machine Learning and Programming Languages — simplifies the development of specialized kernels that can be much faster than those in general-purpose libraries. Its compiler simiplifies code and automatically optimizes and parallelizes it, converting it into code for execution on recent Nvidia GPUs. (CPUs and AMD GPUs and platforms other than Linux aren’t currently supported.)

“The main challenge posed by our proposed paradigm is that of work scheduling — i.e., how the work done by each program instance should be partitioned for efficient execution on modern GPUs,” Tillet explains in Triton’s documentation website. “To address this issue, the Triton compiler makes heavy use of block-level data-flow analysis, a technique for scheduling iteration blocks statically based on the control- and data-flow structure of the target program. The resulting system actually works surprisingly well: our compiler manages to apply a broad range of interesting optimization automatically.”

The first stable version of Triton, along with tutorials, is available from the project’s GitHub repository.

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Astronomers have spotted x-rays from behind a supermassive black hole

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“This is a really exciting result,” says Edward Cackett, an astronomer at Wayne State University who was not involved with the study. “Although we have seen the signature of x-ray echoes before, until now it has not been possible to separate out the echo that comes from behind the black hole and gets bent around into our line of sight. It will allow for better mapping of how things fall into black holes and how black holes bend the space time around them.”

The release of energy by black holes, sometimes in the form of x-rays, is an absurdly extreme process. And because supermassive black holes release so much energy, they are essentially powerhouses that allow galaxies to grow around them. “If you want to understand how galaxies form, you really need to understand these processes outside the black hole that are able to release these enormous amounts of energy and power, these amazingly bright light sources that we’re studying,” says Dan Wilkins, an astrophysicist at Stanford University and the lead author of the study. 

The study focuses on a supermassive black hole at the center of a galaxy called I Zwicky 1 (I Zw 1 for short), around 100 million light-years from Earth. In supermassive black holes like I Zw 1’s, large amounts of gas fall toward the center (the event horizon, which is basically the point of no return) and tend to flatten out into a disk. Above the black hole, a confluence of supercharged particles and magnetic field activity results in the production of high-energy x-rays.

Some of these x-rays are shining straight at us, and we can observe them normally, using telescopes. But some of them also shine down toward the flat disk of gas and will reflect off it. I Zw 1 black hole’s rotation is slowing down at a higher rate than that seen in most supermassive black holes, which causes surrounding gas and dust to fall in more easily  and feed the black hole from multiple directions. This, in turn, leads to greater x-ray emissions, which is why Wilkins and his team were especially interested.

While Wilkins and his team were observing this black hole, they noticed that the corona appeared to be “flashing.” These flashes, caused by x-ray pulses reflecting off the massive disk of gas, were coming from behind the black hole’s shadow—a place that is normally hidden from view. But because the black hole bends the space around it, the x-ray reflections are also bent around it, which means we can spot them.

The signals were found using two different space-based telescopes optimized to detect x-rays in space: NuSTAR, which is run by NASA, and XMM-Newton, which is run by the European Space Agency.

The biggest implication of the new findings is that they confirm what Albert Einstein predicted in 1963 as part of his theory of general relativity—the way light ought to bend around gargantuan objects like supermassive black holes. 

“It’s the first time we really see the direct signature of the way light bends all the way behind the black hole into our line of sight, because of the way black hole warps space around itself,” says Wilkins. 

“While this observation doesn’t change our general picture of black hole accretion, it is a nice confirmation that general relativity is at play in these systems,” says Erin Kara, an astrophysicist at MIT who was not involved with the study.

Despite the name, supermassive black holes are so far away that they really just look like single points of light, even with state-of-the-art instruments. It’s not going to be possible to take images of all of them the way scientists used the Event Horizon Telescope to capture the shadow of a supermassive black hole in galaxy M87. 

So although it’s early, Wilkins and his team are hopeful that detecting and studying more of these x-ray echoes from behind the bend could help us create partial or even full pictures of distant supermassive black holes. In turn, that could help them unlock some big mysteries around how supermassive black holes grow, sustain entire galaxies, and create environments where the laws of physics are pushed to the limit.  

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Sean Gallagher and an AI expert talk today about our crazy machine-learning adventure

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We’ve spent the past few weeks burning copious amounts of AWS compute time trying to invent an algorithm to parse Ars’ front-page story headlines to predict which ones will win an A/B test—and we learned a lot. One of the lessons is that we—and by “we,” I mainly mean “me,” since this odyssey was more or less my idea—should probably have picked a less, shall we say, ambitious project for our initial outing into the machine-learning wilderness. Now, a little older and a little wiser, it’s time to reflect on the project and discuss what went right, what went somewhat less than right, and how we’d do this differently next time.

Our readers had tons of incredibly useful comments, too, especially as we got into the meaty part of the project—comments that we’d love to get into as we discuss the way things shook out. The vagaries of the edit cycle meant that the stories were being posted quite a bit after they were written, so we didn’t have a chance to incorporate a lot of reader feedback as we went, but it’s pretty clear that Ars has some top-shelf AI/ML experts reading our stories (and probably groaning out loud every time we went down a bit of a blind alley). This is a great opportunity for you to jump into the conversation and help us understand how we can improve for next time—or, even better, to help us pick smarter projects if we do an experiment like this again!

Our chat kicks off today, July 28, at 1:00 pm Eastern Time (that’s 10:00 am Pacific Time and 17:00 UTC). Our three-person panel will consist of Ars Infosec Editor Emeritus Sean Gallagher and me, along with Amazon Senior Principal Technical Evangelist (and AWS expert) Julien Simon. If you’d like to register so that you can ask questions, use this link here; if you just want to watch, the discussion will be streamed on the Ars Twitter account and archived as an embedded video on this story’s page. Register and join in or check back here after the event to watch!


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