NVIDIA addresses Spectre vulnerabilities

Subject: General Tech, Graphics Cards | January 5, 2018 - 02:59 PM |
Tagged: meltdown, spectre, geforce, quadro, NVS, nvidia, tesla, security

If you were wondering if NVIDIA products are vulnerable to some of the latest security threats, the answer is yes.  Your Shield device or GPU is not vulnerable to CVE-2017-5754, aka Meltdown, however the two variants of Spectre could theoretically be used to infect you. 

  • Variant 1 (CVE-2017-5753): Mitigations are provided with the security update included in this bulletin. NVIDIA expects to work together with its ecosystem partners on future updates to further strengthen mitigations.

  • Variant 2 (CVE-2017-5715): Mitigations are provided with the security update included in this bulletin. NVIDIA expects to work together with its ecosystem partners on future updates to further strengthen mitigations.

  • Variant 3 (CVE-2017-5754): At this time, NVIDIA has no reason to believe that Shield TV/tablet is vulnerable to this variant.

The Android based Shield tablet should be updated to Shield Experience 5.4, which should arrive before the end of the month.  Your Shield TV, should you actually still have a working on will receive Shield Experience 6.3 along the same time frame.

The GPU is a little more complex as there are several product lines and OSes which need to be dealt with.  There should be a new GeForce driver appearing early next week for gaming GPUs, with HPC cards receiving updates on the dates you can see below.

nvidia patch.PNG

There is no reason to expect Radeon and Vega GPUs to suffer from these issues at this time.  Intel could learn a bit from NVIDIA's response, which has been very quick and includes ther older hardware.

Source: NVIDIA

Gigabyte's Aorus GTX 1070, the GPU you don't unbox

Subject: Graphics Cards | December 28, 2017 - 03:32 PM |
Tagged: external gpu, gigabyte, aorus, gtx 1070, thunderbolt 3, nvidia, gaming box

Have a laptop with Thunderbolt 3 and a mobile GPU that just doesn't cut it anymore?  Gigabyte now offers an incredibly easy way to upgrade your laptop, with no screwdriver required!  The Aorus GTX 1070 Gaming Box contains an external desktop class GTX 1070 and separate PSU, giving you a dock with some serious gaming prowess.  The Tech Report's benchmarks compare this external GPU against the GTX 1060 installed in their Alienware gaming laptop and Alienware's own external GPU enclosure, on both the internal display and an external monitor.  The results are somewhat mixed and worth reading through fully, however if you are on an integrated GPU then this solution is an incredible upgrade.

front34.jpg

"Gigabyte's Aorus GTX 1070 Gaming Box offers us a look into a future where a big shot of graphics performance is just a single cable away for ultraportable notebook PCs. We plugged the Gaming Box into a test notebook and gave it a spin to see just how bright that future looks."

Here are some more Graphics Card articles from around the web:

Graphics Cards

Podcast #481 - NVIDIA TITAN V Deep Learning, NVIDIA EULA Changes, and more!

Subject: General Tech | December 28, 2017 - 11:43 AM |
Tagged: video, titan v, seasonic, nvidia, gtx 1080 ti, asus, amd, 850W, podcast

PC Perspective Podcast #481 - 12/27/17

Join us for discussion on NVIDIA TITAN V deep learning, NVIDIA EULA Changes, and more!

You can subscribe to us through iTunes and you can still access it directly through the RSS page HERE.

The URL for the podcast is: http://pcper.com/podcast - Share with your friends!

Hosts: Ryan Shrout, Josh Walrath, Ken Addison

Peanut Gallery: Alex Lustenberg

Program length: 1:21:32

Podcast topics of discussion:
  1. Week in Review:
  2. News items of interest:
    1. 1:09:00 NVIDIA EULA Reprise
  3. Picks of the Week:
  4. Closing/outro

Source:

AMD, a little too far ahead of the curve again?

Subject: General Tech | December 27, 2017 - 11:42 AM |
Tagged: nvidia, Intel, HBM2, deep learning

AMD has never been afraid to try new things, from hitting 1GHz first, to creating a true multicore processor, most recently adopting HBM and HBM2 into their graphics cards.  That move contributed to some of their recent difficulties with the current generation of GPUs; HBM is more expensive to produce and more of a challenge to implement.  While they were the first to implement HBM, it is NVIDIA and Intel which are benefiting from AMD's experimental nature.  Their new generation of HPC solutions, the Tesla P100, Quadro GP 100 and Lake Crest all use HBM2 and benefit from the experience Hynix, Samsung and TSMC gained fabbing the first generation.  Vega products offer slightly less memory bandwidth as well as lagging behind in overall performance, a drawback to being first.

On a positive note, AMD have now had more experience designing chips which make use of HBM and this could offer a new hope for the next generation of cards, both gaming and HPC flavours.  DigiTimes briefly covers the two processes manufacturers use in the production of HBM here.

_id1460366655_343178_1.jpg

"However, Intel's release of its deep-learning chip, Lake Crest, which came following its acquisition of Nervana, has come with HMB2. This indicates that HBM-based architecture will be the main development direction of memory solutions for HPC solutions by GPU vendors."

Here is some more Tech News from around the web:

Tech Talk

 

Source: DigiTimes

Podcast #480 - NVIDIA TITAN V Compute, Crucial MX500, and more!

Subject: General Tech | December 21, 2017 - 12:19 PM |
Tagged: podcast, x299, v-sync, titan v, sapphire, rx vega, optimus, nvidia, nitro+, MX500, msi, Intel, evga, crucial, CB-C55, AUKEY, ataribox, AT&T, apple, video

PC Perspective Podcast #480 - 12/21/17

Join us for discussion on NVIDIA TITAN V Compute, Crucial MX500, and more!

You can subscribe to us through iTunes and you can still access it directly through the RSS page HERE.

The URL for the podcast is: http://pcper.com/podcast - Share with your friends!

Hosts: Ryan Shrout, Jeremy Hellstrom, Sebastion Peak, Allyn Malventano

Peanut Gallery: Ken Addison, Alex Lustenberg

Program length: 1:32:27

Podcast topics of discussion:

  1. Week in Review:
  2. News items of interest:
    1. 1:04:35 SAPPHIRE Releases NITRO+ Radeon RX Vega (64 & 56)
  3. Picks of the Week:
    1. 1:19:10 Ryan: HP Envy x360 Ryzen 5
    2. 1:24:35 Sebastian: Cooperstand Ecco-G
    3. 1:26:15 Allyn: IOT all of the tings! (16-relay Arduino)
  4. Closing/outro

Source:

How deep is your learning?

Recently, we've had some hands-on time with NVIDIA's new TITAN V graphics card. Equipped with the GV100 GPU, the TITAN V has shown us some impressive results in both gaming and GPGPU compute workloads.

However, one of the most interesting areas that NVIDIA has been touting for GV100 has been deep learning. With a 1.33x increase in single-precision FP32 compute over the Titan Xp, and the addition of specialized Tensor Cores for deep learning, the TITAN V is well positioned for deep learning workflows.

In mathematics, a tensor is a multi-dimensional array of numerical values with respect to a given basis. While we won't go deep into the math behind it, Tensors are a crucial data structure for deep learning applications.

07.jpg

NVIDIA's Tensor Cores aim to accelerate Tensor-based math by utilizing half-precision FP16 math in order to process both dimensions of a Tensor at the same time. The GV100 GPU contains 640 of these Tensor Cores to accelerate FP16 neural network training.

It's worth noting that these are not the first Tensor operation-specific hardware, with others such as Google developing hardware for these specific functions.

Test Setup

  PC Perspective Deep Learning Testbed
Processor AMD Ryzen Threadripper 1920X
Motherboard GIGABYTE X399 AORUS Gaming 7
Memory 64GB Corsair Vengeance RGB DDR4-3000 
Storage Samsung SSD 960 Pro 2TB
Power Supply Corsair AX1500i 1500 watt
OS Ubuntu 16.04.3 LTS
Drivers AMD: AMD GPU Pro 17.50
NVIDIA: 387.34

For our NVIDIA testing, we used the NVIDIA GPU Cloud 17.12 Docker containers for both TensorFlow and Caffe2 inside of our Ubuntu 16.04.3 host operating system.

AMD testing was done using the hiptensorflow port from the AMD ROCm GitHub repositories.

For all tests, we are using the ImageNet Large Scale Visual Recognition Challenge 2012 (ILSVRC2012) data set.

Continue reading our look at deep learning performance with the NVIDIA Titan V!!

Author:
Manufacturer: NVIDIA

Looking Towards the Professionals

This is a multi-part story for the NVIDIA Titan V:

Earlier this week we dove into the new NVIDIA Titan V graphics card and looked at its performacne from a gaming perspective. Our conclusions were more or less what we expected - the card was on average ~20% faster than the Titan Xp and about ~80% faster than the GeForce GTX 1080. But with that $3000 price tag, the Titan V isn't going to win any enthusiasts over.

What the Titan V is meant for in reality is the compute space. Developers, coders, engineers, and professionals that use GPU hardware for research, for profit, or for both. In that case, $2999 for the Titan V is simply an investment that needs to show value in select workloads. And though $3000 is still a lot of money, keep in mind that the NVIDIA Quadro GP100, the most recent part with full-performance double precision compute from the Pascal chip, is still selling for well over $6000 today. 

IMG_5009.JPG

The Volta GV100 GPU offers 1:2 double precision performance, equating to 2560 FP64 cores. That is a HUGE leap over the GP102 GPU used on the Titan Xp that uses a 1:32 ratio, giving us just 120 FP64 cores equivalent.

  Titan V Titan Xp GTX 1080 Ti GTX 1080 GTX 1070 Ti GTX 1070 RX Vega 64 Liquid Vega Frontier Edition
GPU Cores 5120 3840 3584 2560 2432 1920 4096 4096
FP64 Cores 2560 120 112 80 76 60 256 256
Base Clock 1200 MHz 1480 MHz 1480 MHz 1607 MHz 1607 MHz 1506 MHz 1406 MHz 1382 MHz
Boost Clock 1455 MHz 1582 MHz 1582 MHz 1733 MHz 1683 MHz 1683 MHz 1677 MHz 1600 MHz
Texture Units 320 240 224 160 152 120 256 256
ROP Units 96 96 88 64 64 64 64 64
Memory 12GB 12GB 11GB 8GB 8GB 8GB 8GB 16GB
Memory Clock 1700 MHz MHz 11400 MHz 11000 MHz 10000 MHz 8000 MHz 8000 MHz 1890 MHz 1890 MHz
Memory Interface 3072-bit
HBM2
384-bit G5X 352-bit G5X 256-bit G5X 256-bit 256-bit 2048-bit HBM2 2048-bit HBM2
Memory Bandwidth 653 GB/s 547 GB/s 484 GB/s 320 GB/s 256 GB/s 256 GB/s 484 GB/s 484 GB/s
TDP 250 watts 250 watts 250 watts 180 watts 180 watts 150 watts 345 watts 300 watts
Peak Compute 12.2 (base) TFLOPS
14.9 (boost) TFLOPS
12.1 TFLOPS 11.3 TFLOPS 8.2 TFLOPS 7.8 TFLOPS 5.7 TFLOPS 13.7 TFLOPS 13.1 TFLOPS
Peak DP Compute 6.1 (base) TFLOPS
7.45 (boost) TFLOPS
0.37 TFLOPS 0.35 TFLOPS 0.25 TFLOPS 0.24 TFLOPS 0.17 TFLOPS 0.85 TFLOPS 0.81 TFLOPS
MSRP (current) $2999 $1299 $699 $499 $449 $399 $699 $999

The current AMD Radeon RX Vega 64, and the Vega Frontier Edition, all ship with a 1:16 FP64 ratio, giving us the equivalent of 256 DP cores per card.

Test Setup and Benchmarks

Our testing setup remains the same from our gaming tests, but obviously the software stack is quite different. 

  PC Perspective GPU Testbed
Processor Intel Core i7-5960X Haswell-E
Motherboard ASUS Rampage V Extreme X99
Memory G.Skill Ripjaws 16GB DDR4-3200
Storage OCZ Agility 4 256GB (OS)
Adata SP610 500GB (games)
Power Supply Corsair AX1500i 1500 watt
OS Windows 10 x64
Drivers AMD: 17.10.2
NVIDIA: 388.59

Applications in use include:

  • Luxmark 
  • Cinebench R15
  • VRay
  • Sisoft Sandra GPU Compute
  • SPECviewperf 12.1
  • FAHBench

Let's not drag this along - I know you are hungry for results! (Thanks to Ken for running most of these tests for us!!)

Continue reading part 2 of our Titan V review on compute performance!!

Podcast #479 - NVIDIA Titan V, AMD Adrenalin, and more!

Subject: General Tech | December 14, 2017 - 12:09 PM |
Tagged: video, vesa, toshiba, titan v, synaptics, Silverstone, shazam, radeon, podcast, PBT, nvidia, nervana, keylogger, jonsbo, Intel, hp, hdr, corsair, Clear ID, apple, amd, Adrenalin, 14tb

PC Perspective Podcast #479 - 12/14/17

Join us for discussion on NVIDIA Titan V, AMD Adrenalin, and more!

You can subscribe to us through iTunes and you can still access it directly through the RSS page HERE.

The URL for the podcast is: http://pcper.com/podcast - Share with your friends!

Hosts: Ryan Shrout, Josh Walrath, Jeremy Hellstrom, Allyn Malventano,

Peanut Gallery: Ken Addison, Alex Lustenberg

Program length: 1:12:23

Podcast topics of discussion:
  1. Week in Review:
  2. 0:38:15 AD:  Hello Fresh
  3. News items of interest:
  4. Picks of the Week:
    1. 1:06:15 Allyn: Authy
  5. Closing/outro

Source:
Author:
Manufacturer: NVIDIA

A preview of potential Volta gaming hardware

This is a multi-part story for the NVIDIA Titan V:

As a surprise to most of us in the media community, NVIDIA launched a new graphics card to the world, the TITAN V. No longer sporting the GeForce brand, NVIDIA has returned the Titan line of cards to where it began – clearly targeted at the world of developers and general purpose compute. And if that branding switch isn’t enough to drive that home, I’m guessing the $2999 price tag will be.

Today’s article is going to look at the TITAN V from the angle that is likely most interesting to the majority of our readers, that also happens to be the angle that NVIDIA is least interested in us discussing. Though targeted at machine learning and the like, there is little doubt in my mind that some crazy people will want to take on the $3000 price to see what kind of gaming power this card can provide. After all, this marks the first time that a Volta-based GPU from NVIDIA has shipped in a place a consumer can get their hands on it, and the first time it has shipped with display outputs. (That’s kind of important to build a PC around it…)

IMG_4999.JPG

From a scientific standpoint, we wanted to look at the Titan V for the same reasons we tested the AMD Vega Frontier Edition cards upon their launch: using it to estimate how future consumer-class cards will perform in gaming. And, just as we had to do then, we purchased this Titan V from NVIDIA.com with our own money. (If anyone wants to buy this from me to recoup the costs, please let me know! Ha!)

  Titan V Titan Xp GTX 1080 Ti GTX 1080 GTX 1070 Ti GTX 1070 RX Vega 64 Liquid Vega Frontier Edition
GPU Cores 5120 3840 3584 2560 2432 1920 4096 4096
Base Clock 1200 MHz 1480 MHz 1480 MHz 1607 MHz 1607 MHz 1506 MHz 1406 MHz 1382 MHz
Boost Clock 1455 MHz 1582 MHz 1582 MHz 1733 MHz 1683 MHz 1683 MHz 1677 MHz 1600 MHz
Texture Units 320 240 224 160 152 120 256 256
ROP Units 96 96 88 64 64 64 64 64
Memory 12GB 12GB 11GB 8GB 8GB 8GB 8GB 16GB
Memory Clock 1700 MHz MHz 11400 MHz 11000 MHz 10000 MHz 8000 MHz 8000 MHz 1890 MHz 1890 MHz
Memory Interface 3072-bit
HBM2
384-bit G5X 352-bit G5X 256-bit G5X 256-bit 256-bit 2048-bit HBM2 2048-bit HBM2
Memory Bandwidth 653 GB/s 547 GB/s 484 GB/s 320 GB/s 256 GB/s 256 GB/s 484 GB/s 484 GB/s
TDP 250 watts 250 watts 250 watts 180 watts 180 watts 150 watts 345 watts 300 watts
Peak Compute 12.2 (base) TFLOPS
14.9 (boost) TFLOPS
12.1 TFLOPS 11.3 TFLOPS 8.2 TFLOPS 7.8 TFLOPS 5.7 TFLOPS 13.7 TFLOPS 13.1 TFLOPS
MSRP (current) $2999 $1299 $699 $499   $399 $699 $999

The Titan V is based on the GV100 GPU though with some tweaks that lower performance and capability slightly when compared to the Tesla-branded equivalent hardware. Though our add-in card iteration has the full 5120 CUDA cores enabled, the HBM2 memory bus is reduced from 4096-bit to 3072-bit and it has one of the four stacks on the package disabled. This also drops the memory capacity from 16GB to 12GB, and memory bandwidth to 652.8 GB/s.

Continue reading our gaming review of the NVIDIA Titan V!!

Video: What does a $3000 GPU look like? NVIDIA TITAN V Unboxing and Teardown!

Subject: Graphics Cards | December 12, 2017 - 07:51 PM |
Tagged: nvidia, titan, titan v, Volta, video, teardown, unboxing

NVIDIA launched the new Titan V graphics card last week, a $2999 part targeted not at gamers (thankfully) but instead at developers of machine learning applications. Based on the GV100 GPU and 12GB of HBM2 memory, the Titan V is an incredibly powerful graphics card. We have every intention of looking at the gaming performance of this card as a "preview" of potential consumer Volta cards that may come out next year. (This is identical to our stance of testing the Vega Frontier Edition cards.)

But for now, enjoy this unboxing and teardown video that takes apart the card to get a good glimpse of that GV100 GPU.

A couple of quick interesting notes:

  • This implementation has 25% of the memory and ROPs disabled, giving us 12GB of HBM2, a 3072-bit bus, and 96 ROPs.
  • Clock speeds in our testing look to be much higher than the base AND boost ratings.
  • So far, even though the price takes this out of the gaming segment completely, we are impressed with some of the gaming results we have found.
  • The cooler might LOOK the same, but it definitely is heavier than the cooler and build for the Titan Xp.
  • Champagne. It's champagne colored.
  • Double precision performance is insanely good, spanking the Titan Xp and Vega so far in many tests.
  • More soon!

gv100.png

Source: NVIDIA