Showing posts with label CUDA. Show all posts
Showing posts with label CUDA. Show all posts

Monday, June 1, 2020

A is for Ampere, Nvidia A100's Public Debut

NOTE:  The publication of this episode was delayed due to the untimely passing of our partner and pal Rich Brueckner. So what we’re announcing as "breaking news" isn’t so fresh today, but our takes on what NVIDIA’s new A100 processor brings to the table are still valid. 


Breaking News! This special edition of RadioFreeHPC takes a deep dive into NVIDIA’s spanking new A100 GPU – which is an impressive achievement in processor-dom. The new chip is built with a 7nm process and weighs in at a hefty 54 billion transistors and capped at 400 Watts. It sports 6,912 FP32 CUDA cores, 3,456 FP64 CUDA cores and 422 Tensor cores.
This 8th generation GPU, using what the company calls its Ampere technology, is a replacement for both their V100 GPU and Turing T4 processors, giving the company a single platform for both AI training and inferencing.
We talk about the specs of the A100, breaking down its game both in terms of typical HPC FP64 processing and FP32 (and lower precision) computing for AI workloads. On the HPC side, the new GPU seems to offer an across the board 25% speedup, which is substantial. But the A100 really shines when it comes to tensor core performance which the company reports at an average speed up of 10x on Tensor Core 32 bit vs. V100 FP32.
New features of the A100 include Sparsity (a mechanism that doubles sparse matrix performance), a much speedier NVLink (2x), and a hardware feature that allows the A100 to be partitioned into as many as 7 GPU instances to support individual workloads.
All in all, this is an amazing new processor, a behemoth large and hot, but so fast, chip that is heavily tilted towards new AI and Tensor workloads with a passing but welcome nod to 64-bit HPC apps.

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Monday, March 16, 2020

One Big Debate over OneAPI

For RF-HPC aficionados, it’s a typical opening for this episode. Henry is counting down the days until he moves to sunny Los Cruces and we have a lull in the conversation right after the introductions. We recover quickly and move onto the main course of today’s show:

Intel’s OneAPI project

The OneAPI project is a highly ambitious initiative; trying to design a single API to handle CPUs, GPUs, FPGAs, and other types of processors. In the discussion, we look under the hood and see how this might work. One thing working in Intel’s favor is that they’re using data parallel C++, which is highly compatible with CUDA – and which is probably Intel’s target with this new initiative.

Henry points out that porting codes is a pain and that no one wants to port to another API if it can possibly be avoided, so he predicts that most customers will not want to use it and if they consider it, before they move any code, they need to be sure that this new API is going to stick around for many years.

Shahin is generally positive on the project. Henry and Dan to have a rare moment of agreement in disputing Shahin’s thoughts about several things! Let's start with his view that Java has provided portability in exchange for performance – and then improved its performance. Henry and Dan take issue with this, with Henry saying that Java provides little real performance and Dan saying that programs have changed to provide Java performance rather than Java changing to provide performance. Shahin believes that OneAPI is a good thing for the industry and will be successful. Dan believes it’s a good thing for Intel, but has doubts about whether it’s good for the industry. Henry doesn’t see big adoption for the foreseeable future saying, “It has a long way to go and it’s a significant risk.” Dan and Henry end up agreeing and agreeing to disagree with Shahin. Jessi is safely on the fence on this one.

It’s a very good conversation, well worth a listen.

Why Nobody Should Ever be Online. Ever.

This week, Henry shares a personal story about key fobs and a very troubling problem he found with his latest rental car. It has everything, thrills, chills and a shocking conclusion.

Catch of the Week

Jessi:  The Department of Defense has built a supercomputer in a shipping container, for sending to wherever its computation is needed. The supercomputer itself is designed to work on AI-related problems, and falls under the classification of "AI on the edge," where data is processed in the same location it is collected. While it’s not news, it’s news to Jessi and it’s cool, so it’s her catch of the week.

Shahin:  Tells the story of a reporter renting a shared car service, which is unlocked by a cell phone. The reporter ventures out into the hinterlands a little bit and finds that she can’t get the car to work anymore. Why? Because there wasn’t enough cell phone coverage to properly start the car – meaning that the reporter had to wait (and wait) for a person to be sent out to physically interact with the car and get it going again. Yikes – think out your products, people, ok?

Henry:  Hackers made a home for themselves inside Citrix for five months, siphoning off personal and financial information. Yikes again. The company had to be alerted by the FBI to the hack and, assumedly, their internal tools didn’t pick up the penetration. That’s a long time to be exploited!

Dan:  McAfee researchers show that just a few strips of tape on a road sign can prompt a Tesla car to accelerate by an astounding 50 miles per hour over the posted speed limit on that sign. According to Dan, this is a bad thing.

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