Spectre 3a and Spectre 4 Unfortunately Announced...

Subject: Processors | May 22, 2018 - 07:51 PM |
Tagged: x86, arm, Intel, amd, spectre

Security researchers at Microsoft and Google have found two new vulnerabilities along the lines of the Spectre and Meltdown bugs from early January. These are being called Spectre 3a (Rogue System Register Read) and Spectre 4 (Speculative Store Bypass). Like last time, hardware and software vendors have addressed the issues, which will be coming down via OS updates.

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Naturally, James Bond will steal information when there's Intel Inside.

On the AMD side of things, they claim that the Spectre 4 vulnerability will be patched as far back as Bulldozer (2011). They also claim that no action will be necessary, at least to their knowledge, for Spectre 3a on their x86 parts. They have also released a short, five-page whitepaper discussing the issue.

On the Intel side of things… a security bulletin has been posted for CPUs as far back as Nehalem. They don’t exactly clarify which processors are susceptible to which vulnerabilities, but they acknowledge that both Spectre 3a and Spectre 4 touch something on their product stack to some extent. They have submitted a beta microcode update to OS vendors, which they expect to be production ready “in the coming weeks”.

ARM is also affected to some extent. They have published a table that lists which architectures are vulnerable to what exploit. Interestingly, there are some processors that are vulnerable to 3a, but not 4, and others that are vulnerable to 4, but not 3a (and, of course, some that are vulnerable to both and neither). Since these exploits are based on optimizations gone awry, you would think that it would have built up over time, but that doesn’t seem to be the case. The only pattern I could notice is that Variant 4 only affects newish 64-bit ARM processors. I don’t know if that’s a red herring, or a well-known corollary of the bug that I just don’t know enough about, but it’s about all that I can see.

Regardless, expect patches soon, which might, again, lower performance by some amount.

Podcast #499 - Onyx Boox, BitFenix, and more!

Subject: General Tech | May 10, 2018 - 04:35 PM |
Tagged: podcast, velocity micro, qualcomm, Portal, Onyx Boox, nvidia, Netflix, microsoft, linux, K63, Intel, hyperx, google, evga, corsair, coolermaster, ChromeOS, bitfenix, arm, amd, 4k, video

PC Perspective Podcast #499 - 05/10/18

Join us this week for discussion on Onyx Boox, a slick BitFenix case, 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: Allyn Malventano, Jeremy Hellstrom, Josh Walrath, Ken Addison,

Peanut Gallery: Alex Lustenberg

Program length: 1:01:13

Podcast topics of discussion:

  1. Week in Review:
  2. News items of interest:
  3. Picks of the Week:
    1. 0:47:40 Jeremy:Building a Ryzen on a budget eh?
    2. 0:50:10 Josh:I have issues.   We know
    3. 0:52:20 Allyn: System monitoring Gadgets. On Windows 10. Good ones.
  4. Closing/outro
 
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Podcast #498 - Microsoft Surface Book 2, Intel 905P Optane, and more!

Subject: General Tech | May 3, 2018 - 09:19 AM |
Tagged: windows 10, video, surface, podcast, Oculus, Nocutua, microsoft, kaby lake-x, Jim Keller, Intel, coolermaster, arm

PC Perspective Podcast #498 - 05/03/18

Join us this week for discussion on Microsoft Surface Book 2, Intel 905P Optane, 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, Allyn Malventano, Jeremy Hellstrom, Josh Walrath

Peanut Gallery: Ken Addison, Alex Lustenberg

Program length: 1:31:26

Podcast topics of discussion:
  1. Week in Review:
  2. Casper
  3. News items of interest:
  4. Picks of the Week:
    1. 1:21:20 Ryan: Oculus Go
    2. 1:22:20 Jeremy: Great deal on a B350
    3. 1:26:25 Allyn: Got a Vive? Buy a Gear VR cheap! (and do some modding with these)
  5. Closing/outro
 
Source:

ARM Introduces Physical Security to Cortex-M Line

Subject: General Tech | May 2, 2018 - 11:00 AM |
Tagged: voltage, physical attacks, exploits, EM, CryptoIsland, CryptoCell, Cortex-M35P, cortex, arm

 

The world is rife with exploits. We see and hear about them everyday. It is a major problem for device makers that try to use cutting edge technology in their products, but do not know what potential vulnerabilities can be exposed. ARM has a robust security suite available for their chips that can be licensed and implemented, but so far these have dealt primarily with software. Nothing has been done in consumer chips to protect from other side-channel exploits in which the chip is physically accessed.

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Physical security was once the realm of military style hardware that were hardened and designed to be nearly impervious if falling into the wrong hands. Now ARM is offering partners the ability to implement several physical security features into their chips to help defeat those who wish to exploit these products.

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The first product to get this treatment is the new Cortex-M35P. This is based on previously released Cortex-M3x technology featuring the Armv8-M ISA. It is a new chip in that it has all of the features for physical security integrated into the design. It also features all of the previous security IP that ARM has released including TrustZone, CryptoIsland, and CryptoCell.

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Physcial attacks can come through a variety of ways. Monitoring voltage and EM from the chip is the least invasive, while physically accessing the device and exposing the core down to the transistor level obviously destroys the chip but gives the attacker a lot of information about the chip. The former attacks can be done by people with varying levels of experience and commonly acquired tools. The latter attack requires a tremendous amount of knowledge as well as require high end equipment not normally found outside of chip design and fabrication firms. ARM cannot protect against dissecting the part, but they can help protect against the more non-invasive exploits.

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EM and voltage monitoring can give clues about potential sideband exploits that would work with the chip. The attacker records these measurements when the chip is doing work such as encryption. This then can lead to more specific attacks on the chip. ARM is able to design countermeasures on these chips to either limit EM output or to “dirty” the output so that it reveals little about the operation of the chip. ARM is able to do much the same when it comes to voltage tampering.

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ARM did not go into any significant detail on the actual mechanisms of these security features. All we know is that these are features designed into the chip from the beginning and cannot be applied retroactively to previous chips. This makes sense due to these being physical attacks, and if ARM detailed the countermeasures, then the attackers can more easily work around them.

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Security is a process. One fix will not create a totally locked-down world. It takes a pretty extensive infrastructure to address all of the threats that are likely to be encountered by IoT devices throughout the world. Adding to the physical IP with security measures allows ARM and its clients to be that little bit more confident that they are exposing their users to the least amount of risk possible when it comes to exploiting these products.

Source: ARM

GTC 2018: Nvidia and ARM Integrating NVDLA Into Project Trillium For Inferencing at the Edge

Subject: General Tech | March 29, 2018 - 03:10 PM |
Tagged: project trillium, nvidia, machine learning, iot, GTC 2018, GTC, deep learning, arm, ai

During GTC 2018 NVIDIA and ARM announced a partnership that will see ARM integrate NVIDIA's NVDLA deep learning inferencing accelerator into the company's Project Trillium machine learning processors. The NVIDIA Deep Learning Accelerator (NVDLA) is an open source modular architecture that is specifically optimized for inferencing operations such as object and voice recognition and bringing that acceleration to the wider ARM ecosystem through Project Trillium will enable a massive number of smarter phones, tablets, Internet-of-Things, and embedded devices that will be able to do inferencing at the edge which is to say without the complexity and latency of having to rely on cloud processing. This means potentially smarter voice assistants (e.g. Alexa, Google), doorbell cameras, lighting, and security around the home and out-and-about on your phone for better AR, natural translation, and assistive technologies.

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Karl Freund, lead analyst for deep learning at Moor Insights & Strategy was quoted in the press release in stating:

“This is a win/win for IoT, mobile and embedded chip companies looking to design accelerated AI inferencing solutions. NVIDIA is the clear leader in ML training and Arm is the leader in IoT end points, so it makes a lot of sense for them to partner on IP.”

ARM's Project Trillium was announced back in February and is a suite of IP for processors optimized for parallel low latency workloads and includes a Machine Learning processor, Object Detection processor, and neural network software libraries. NVDLA is a hardware and software platform based upon the Xavier SoC that is highly modular and configurable hardware that can feature a convolution core, single data processor, planar data processor, channel data processor, and data reshape engines. The NVDLA can be configured with all or only some of those elements and they can independently them up or down depending on what processing acceleration they need for their devices. NVDLA connects to the main system processor over a control interface and through two AXI memory interfaces (one optional) that connect to system memory and (optionally) dedicated high bandwidth memory (not necessarily HBM but just its own SRAM for example).

arm project trillium integrates NVDLA.jpg

NVDLA is presented as a free and open source architecture that promotes a standard way to design deep learning inferencing that can accelerate operations to infer results from trained neural networks (with the training being done on other devices perhaps by the DGX-2). The project, which hosts the code on GitHub and encourages community contributions, goes beyond the Xavier-based hardware and includes things like drivers, libraries, TensorRT support (upcoming)  for Google's TensorFlow acceleration, testing suites and SDKs as well as a deep learning training infrastructure (for the training side of things) that is compatible with the NVDLA software and hardware, and system integration support.

Bringing the "smarts" of smart devices to the local hardware and closer to the users should mean much better performance and using specialized accelerators will reportedly offer the performance levels needed without blowing away low power budgets. Internet-of-Things (IoT) and mobile devices are not going away any time soon, and the partnership between NVIDIA and ARM should make it easier for developers and chip companies to offer smarter (and please tell me more secure!) smart devices.

Also read:

Source: NVIDIA

ARM Introduces Kigen OS for Cellular IoT

Subject: General Tech | February 21, 2018 - 09:00 AM |
Tagged: modem, Kigen, iSIM, iot, cortex, cellular, arm

Last year ARM went on a bit of a buying spree thanks to the financial help of its holding company, SoftBank. One of the companies that it scooped up was that of Simulity Labs for around 12 million pounds. The company was developing IoT security products based on eSIM technology and a robust OS that provides provisioning on a cellular network.

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Many believe that the nearly ubiquitous cellular networks that surround us are the key to truly successful IoT products. There are massive cellular deployments around the world. It is a well regulated spectrum. Security through SIM cards is a well known and understood process. It is not impossible to break this security, but it is questionable if it is worth the time and effort to do so.

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ARM has gone ahead and provided the means to productize and push this technology with the aim of providing a vast, secure IoT infrastructure that would be relatively easy to rollout with current cellular networks. There are multiple parts to this technology, but ARM is hoping to offer an all-in-one solution that would provide an inexpensive platform for OEMs and Mobile Network Operators (MNOs) to roll out products on.

Click here to read the rest of our coverage of ARM Kigen and iSIM!

Source: ARM

Windows 10 on ARM Details

Subject: General Tech | February 19, 2018 - 01:22 PM |
Tagged: microsoft, windows 10, qualcomm, arm

Paul Thurrott found a developer documentation page, Troubleshooting x86 Desktop Apps, on the Windows Dev Center. The goal of the page is to list a few reasons why the software you develop might not be compatible with Windows 10 on ARM and the WOW translation layer. Yup, they’re reusing that name, which was the translation layer for 32-bit Win32 applications running on 64-bit Windows.

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Based on this document, we now know that Windows on ARM:

  • Will not translate x86 drivers, just x86 applications and services.
  • Does not support 64-bit applications (Thurrott.com says they’re working on it.)
  • Does not support (hardware-accelerated) OpenGL 1.1+ or DirectX 1-8
    • Vulkan is not mentioned anywhere, but I’m guessing not.

There are also a few other issues, like the application cannot modify Windows components (ex: the 7-zip entry in the Windows file explorer’s right-click menu) unless it is recompiled for ARM. Thurrott.com also says that Hyper-V is not supported in Windows 10 on ARM.

The amount of software that Windows on ARM can run is surprisingly both broader and narrower than I would have expected. The major issue for me is OpenGL – you would think that the graphics driver would dictate this, not so much the OS APIs. I certainly hope that, especially after their other pushes toward openness, Microsoft isn’t pressuring ARM manufacturers to not ship an OpenGL driver, even though the hardware vendors clearly know how to support OpenGL ES at the very least.

And yes, there could very well be a good reason, and they might even be working on OpenGL support as we speak, but it’s an odd omission (at least for now).

Lastly, this has nothing to do with UWP applications. This document is only about standard Win32 applications running on ARM processors. UWP is designed to be cross-architecture. You just need to include the ARM target when you build and package.

Source: Microsoft

Podcast #487 - AMD Desktop APUs, Snapdragon 845, ARM Machine Learning, and more!

Subject: General Tech | February 15, 2018 - 11:32 AM |
Tagged: podcast, Intel, amd, nvidia, raven ridge, r5 2400g, r3 2200g, arm, project trillium, qualcomm, snapdragon 845, x24, LTE, 5G

PC Perspective Podcast #487 - 02/15/18

Join us this week for a recap of news and reviews including new AMD Desktop APUs, Snapdragon 845 Performance Preview, ARM Machine Learning, 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, Josh Walrath, Allyn Malventano

Peanut Gallery: Alex Lustenberg, Ken Addison

Program length: 1:18:46

Podcast topics of discussion:

  1. Week in Review:
  2. News items of interest:
  3. Picks of the Week:
    1. 1:09:00 Jeremy: &genie=1
  4. Closing/outro
 
Author:
Subject: General Tech
Manufacturer: ARM

Addressing New Markets

Machine Learning is one of the hot topics in technology, and certainly one that is growing at a very fast rate. Applications such as facial recognition and self-driving cars are powering much of the development going on in this area. So far we have seen CPUs and GPUs being used in ML applications, but in most cases these are not the most efficient ways of doing these highly parallel but relatively computationally simple workloads. New chips have been introduced that are far more focused on machine learning, and now it seems that ARM is throwing their hat into the ring.

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ARM is introducing three products under the Project Trillium brand. It features a ML processor, a OD (Object Detection) processor, and a ARM developed Neural Network software stack. This project came as a surprise for most of us, but in hindsight it is a logical avenue for them to address as it will be incredibly important moving forward. Currently many applications that require machine learning are not processed at the edge, namely in the consumer’s hand or device right next to them. Workloads may be requested from the edge, but most of the heavy duty processing occurs in datacenters located all around the world. This requires communication, and sometimes pretty hefty levels of bandwidth. If neither of those things are present, applications requiring ML break down.

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Click here to read the rest of the article about Project Trillium!

CES 2018: Lenovo Joins the Windows on ARM Rush with the 12-inch Miix 630 2-in-1 PC

Subject: Mobile | January 8, 2018 - 08:00 PM |
Tagged: WOA, windows on arm, snapdragon 835, snapdragon, qualcomm, Lenovo, laptop, convertible, CES 2017, arm, 2-in-1

Lenovo today unveiled the Miix 630, a 12-inch Windows 10 S device powered by Qualcomm's Snapdragon 835 processor. With the Miix 630, Lenovo joins HP, ASUS, and other manufacturers in the new Windows on ARM product category of ultraportable, always connected PCs and tablets.

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The Miix 630 is powered by the Qualcomm Snapdragon 835 with integrated Adreno 540 graphics. It features a 12.3-inch 1920x1280 touchscreen display which, when paired with the included Lenovo pen, offers up to 1,024 levels of pressure sensitivity for drawing and writing. Other features include a 5MP front facing infrared camera with Windows Hello support, 13MP rear camera, detachable backlit keyboard with touchpad, and integrated LTE for the "always on" feature that distinguishes these devices from those with traditional mobile connectivity options.

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Despite its "always on" capabilities, the Miix 630 joins other Windows on ARM devices in touting lengthy battery life, with negligible battery draw while in standby mode and actual usage time of 20 hours for tasks such as continuous video playback.

The Miix 630's complete specs:

Processor Qualcomm Snapdragon 835
Graphics Adreno 540
Micrphones 2
Speakers 2 x 1 watt
Memory 4GB / 8GB
Storage 64GB / 128GB / 256GB
Battery 48 Whr
Display 12.3-inch
WUXGA+ (1920 x 1280)
Corning Glass Screen
Ports 1 x USB Type-C
1 x 3.5mm Audio In/Out
1 x SD Card
1 x Nano SIM Card
Connectivity 2x2 Wi-Fi 802.11ac
Bluetooth 4.1
LTE Cat11
Dimensions (D) 210mm x (W) 293mm x (H) 15.6mm
Weight 2.93 lbs (1.33 kg)

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Complete pricing for the higher-end configurations is not yet available, but Lenovo states that the Miix 630's base configuration will start at $799. It's expected to launch in the second quarter of this year.

Source: