ASUS Launches The Chromebit CS10 HDMI Stick
Earlier
this year ASUS launched a pair of Chromebooks, and they also teased
another product that would be launching later in the year. It was the
Chromebit HDMI stick, and it's essentially a Chrome OS computer that you
plug into the HDMI port on your monitor or television. ASUS thinks the
Chromebit will be great for applications like digital signage, but
pairing it with a Bluetooth keyboard and mouse allows it to be used as a
consumer Chrome OS computer as well. You can check out the Chromebit
CS10's specs below.
|
ASUS Chromebit CS10 |
| SoC |
Rockchip RK3288-C
4 x Cortex A17 + Mali T764 |
| RAM |
2 GB LPDDR3 |
| NAND |
16GB NAND |
| Dimensions / Mass |
123 x 31 x 17mm, 75g |
| OS |
Chrome OS |
| Other Connectivity |
2x2 802.11a/b/g/n/ac + BT 4.0, HDMI 1.4, USB 2.0, DC-in |
| Price |
$85 |
A combination of size and price means we're not
going to be seeing something like an Intel Core i5 in an HDMI stick any
time soon. Thankfully, Chrome OS tends to run pretty well even with
minimal hardware power. At $85, the Chromebit CS10 comes with 2GB of
RAM, 16GB of eMMC NAND, dual-band 802.11ac, and a Rockchip RK3288-C SoC.
RK3288-C is a quad core Cortex A17 part paired with a Mali T764 GPU.
The same SoC has actually shown up in some of ASUS's actual Chromebooks
as well, so it's not surprising to see it in the Chromebit.
As
with all HDMI sticks, you still need a separate power adapter because
HDMI 1.4 can't supply nearly enough power for even such a smaller
computer. Even with that, the Chromebit could still make for an
interesting computer of sorts that can be taken anywhere in your pocket.
The ASUS Chromebit CS10 will cost $85, and it comes with a year of 100GB Google Drive space. It'll begin shipping today.
Read More ...
Best Android Phones: Holiday 2015
As
we hit the middle of November, the holiday shopping season is starting
up. As we have for the past several years, this year we are putting
together a series of holiday guides with recommendations for various
product categories and some quick links to those products. These holiday
guides also act as a way for us to look over all the devices that have
been released in a given year to see which still hold up.
We'll
be starting things off this year with smartphones. Smartphones are an
enormous market, and the average phone lifetime still being only 18-24
months, many gifts given this holiday season are going to be
smartphones. So let's take a look at what we believe to be the best
Android phones that you can buy this holiday season.
Best Android Phablet: Samsung Galaxy Note5
The
term phablet is a bit silly in my opinion, but it has become a fairly
common term to describe smartphones with very large profiles. The
definition of a phablet is not exactly concrete, and it mainly has to do
with a device's chassis size. For example, the Nexus 6 and Galaxy Note5
are clearly phablets, and it's fairly safe to say that the iPhone 6s
Plus is one too. However, I don't know if I would describe the LG G4 as a
phablet. It has the same screen size as the iPhone 6S Plus, but the use
of on-screen buttons and smaller overall chassis size mean that it ends
up straddling the line between your standard smartphone and a phablet.
When looking at which devices are available in many regions, I think
it's pretty clear which phablet offers the best value at the absolute
high end, and which offers the best value for someone who is looking to
spend less than what they would on a typical flagship.
I
don't think it would be wrong to say that Samsung really pioneered the
phablet category. The original Galaxy Note was laughed at by many, but
as time has gone on Samsung has improved on it, and now every vendor
offers a similarly sized device. With that in mind, it shouldn't come as
a surprise that
the Galaxy Note5
is my recommendation for a high end phablet. It comes with everything
that makes the Galaxy S6 a great phone, but in a larger size and with
some additional improvements. Just as an overview, you're getting a 5.7"
2560x1440 AMOLED display, Samsung's Exynos 7420 SoC, 4GB of LPDDR4 RAM,
and 32, 64, or 128GB of internal NAND. Some differences from the Galaxy
S6 apart from simply being larger include improved camera image
processing, making it a serious contender for the title of best
smartphone camera, and the inclusion of Samsung's S-Pen for navigation
and drawing.
The Galaxy Note 5 costs $699 for the 32GB version in the US.
There are often deals that can help bring the price down a bit, such as
a recent $50 off offer from T-Mobile. The 64GB model bumps the price to
$779. It's worth noting the prices for the Galaxy S6 Edge+ as well,
which is to the Galaxy Note5 what the Galaxy S6 Edge is to the standard
Galaxy S6. It starts at $779 for 32GB, and $859 for 64GB. I personally
think the edge design looks cool, but there's definitely a trade off in
terms of ergonomics, and I don't think it's worth the additional cost
unless you really want to own Samsung's absolute highest end phone.
For buyers who aren't fans of the Galaxy Note5, or who are looking for something that isn't quite as expensive, the
Nexus 6P
is definitely worth considering. Like the Galaxy Note5 it has a 5.7"
2560x1440 AMOLED display, but inside you get Qualcomm's Snapdragon 810
paired with 3GB of LPDDR4 RAM and 32GB of NAND.
Some
highlights of the Nexus 6P are the camera and the chassis. While we
haven't published our Nexus 6P review yet, it uses the same sensor and
lens arrangement as the Nexus 5X which I felt has one of the best
cameras of any smartphone. The aluminum chassis of the 6P may also be
more appealing than the metal/glass design of the Note5, although I
didn't feel that the design and ergonomics were at the same level as
devices like Huawei's own Mate S or the iPhone 6s Plus.
Of
course, the biggest appeal of the Nexus 6P is its price. At $499 for
32GB, it undercuts most flagship phablets by $200 or so, while being
competitive in many other respects. You definitely lose out on the
performance of Samsung's Exynos 7420 SoC, but there are obviously
tradeoffs that are made when targeting a lower price. The promise of
software updates along with a great camera, an aluminum build, and a
great fingerprint scanner make the Nexus 6P a very worthwhile choice for
a phablet at a lower price than the latest and greatest flagships.
European customers will notice that they get charged a significant
premium for the Nexus 6P, with the 32GB model priced at around 700€. At
that price I would probably consider other devices unless one is
determined to stay with a Nexus phone for the support and updates.
Best High-End Android Smartphone: Samsung Galaxy S6
While
phablets have grown immensely in popularity, the normal flagship
devices from the players in the Android space tend to be smaller than
the 5.7-6.0" displays that ship on phablets. Not having to push a large
size also opens up more opportunities to offer a great device at a lower
price than the competition. Taking that into consideration, I think
there are two key flagship devices that are worth considering if looking
for a flagship phone in a typical size, along with one clear winner for
a smartphone that offers a lot for a lower price than flagship
smartphones.
The
Galaxy S6
really needs no introduction. Along with the Note5 it's really the only
Android phone this year that was able to push the performance of
Android devices forward, courtesy of its Exynos 7420 SoC. Along with
still being the fastest Android phone around, the Galaxy S6 comes with a
top notch 5.1" 2560x1440 AMOLED display, 3GB of LPDDR4 RAM, 32, 64, or
128GB of NAND, and the same 16MP camera that the Galaxy Note5 uses.
It
is a bit disappointing that the Galaxy S6 is still the fastest Android
phone out there many months after it was released. While some may feel
it's actually best to wait for the next generation Galaxy phone from
Samsung, such a launch is still one or two quarters away, and if someone
is looking to get the most powerful Android smartphone for the holidays
the Galaxy S6 is definitely it. As far as the price goes, the fact that
the S6 is a bit older now means you can find some appealing discounts.
Right now on T-Mobile USA you can get the 32GB model for $579, and at
$659 you get 128GB which is a pretty great deal. Like the Note5, I
wouldn't recommend paying the extra money for the Edge version of the
phone unless you really want the more unique design, as the ergonomics
are honestly a downgrade.
If you're looking for something a bit larger, or less expensive than the Galaxy S6,
the LG G4
is definitely worth considering. Although it has a 5.5" display, it's
much smaller than a phone like the iPhone 6s Plus due to its small
bezels on all sides, and the use of on screen buttons. In my experience
it's still a bit too big to be used comfortably in a single hand even
with affordances like the back-mounted volume rocker, but it's not
really a phablet either. As far as its specs go, you get Qualcomm's
Snapdragon 808 SoC, 3GB of LPDDR3 RAM, 32GB of NAND, and a 16MP Sony
IMX234 rear-facing camera. It also has microSD expansion and a removable
battery for the users who were upset with Samsung's removal of those
features on this year's Galaxy flagships.
Price wise,
the LG G4 sells for around $479,
which is about $100 less than you'd pay for the Galaxy S6. The size of
the phone is definitely worth considering in addition to the price, as
the S6 is much easier to use with a single hand, but if you want a phone
with a larger display without moving completely into phablet territory
the G4 is definitely a phone to heavily consider.
Best Mid-Range Android Smartphone: Google Nexus 5X
Next we come to the lower cost high end, and here's there's only one real Android device worth mentioning, the
Nexus 5X. This is actually my personal favorite Android device from this year, and
I published my review of it last week.
In many ways it's similar to the LG G4, which isn't surprising when you
consider that it's made by LG. It has a Qualcomm Snapdragon 808 SoC,
2GB of LPDDR3 RAM, 16 or 32GB of NAND, and the same great 12MP camera
that you get in the Nexus 6P.
To sum up my thoughts on
the Nexus 5X from my review, I'll say that it's imperfect, but I think
it's unbeatable at $379. Snapdragon 808 doesn't deliver the performance
jump that you'd expect from two years of technological advancement since
the Nexus 5, but you still get a great display, an amazing camera, good
battery life, a quick and simple fingerprint scanner, and a plastic but
very solid chassis. The fact that the 5X includes the same camera as
the Nexus 6P
at its $379 price
is really what gives it an edge, and if you're looking to get something
smaller than a phablet without paying the $600-700 commanded by
flagship phones I don't think you can go wrong with the Nexus 5X. Like
the 6P, the 5X is unfortunately more expensive in Europe, coming in at
around 449€, and so in those markets it may be best to consider some
other options.
Best Budget Android Phone: Motorola Moto G (2015)
The
last category on the list is the budget phone, which to me includes
anything from $250 down, although $250 is certainly pushing it. There
are certainly a large number of Android devices that fit this category,
and I'm sure some people will feel that it makes the most sense to look
at importing phones from Xiaomi rather than buying a phone from a more
global brand where you may not get as much for your money. I can only
really speak from experience, and I think importing comes with its own
issues regarding the warranty, customs fees, and carrier compatibility.
There was only one budget device from the big Android players that I
looked at this year and feel is really worth considering, and it's
the 2GB version of the 2015 Moto G.
The
2015 Moto G comes in two versions. Both have a Qualcomm Snapdragon 410
SoC, a Sony IMX214 13MP camera, and a 1280x720 IPS display. However,
while $179 gets you a version with 8GB of NAND and 1GB of RAM,
$219 doubles both of those to 16GB and 2GB respectively.
With the amount of RAM overhead created by Java applications that use
garbage collection I really don't think 1GB is a usable amount of memory
on an Android device unless you're shopping in the sub $100 range where
you're not likely to be using many apps at all. For that reason, I
think the 2GB model is the best budget smartphone, as it includes a
relatively good camera for its price, has enough RAM, and should be fast
enough for the needs of anyone shopping for a smartphone at this price.
It's also waterproof, and has an extremely long battery life.
While
there are other budget Android phones, you end up having to pay
significantly more than the Moto G to get any significant improvement,
and dropping the price even lower ends up coming with a number of
compromises that aren't worth the money you save.
Read More ...
NVIDIA Re-launches the SHIELD Tablet as the SHIELD Tablet K1
The life of the NVIDIA SHIELD Tablet has had some ups and downs.
Josh reviewed it last year,
and at the time he found that NVIDIA's tech for game streaming offered
an interesting value proposition. Unfortunately, NVIDIA was
forced to issue a total recall on the tablets due to overheating concerns earlier this year,
and while they shipped replacement devices to consumers, the SHIELD
Tablet ended up being removed from sale. This was quite unfortunate, and
it left a gap in the Android tablet market that I really haven't seen
any vendor fill.
Today NVIDIA is re-introducing the
SHIELD Tablet with a new name. It's now called the SHIELD Tablet K1,
something I hope implies we will soon see a SHIELD Tablet X1.
While
the name is new, we're looking at the exact same tablet that launched
last year. I've put the specs in the chart below as a refresher.
|
NVIDIA SHIELD Tablet K1 |
| SoC |
NVIDIA Tegra K1 (2.2 GHz 4x Cortex A15r3, Kepler 1 SMX GPU) |
| RAM |
2 GB DDR3L-1866 |
| NAND |
16GB NAND + microSD |
| Display |
8” 1920x1200 IPS LCD |
| Camera |
5MP rear camera, 1.4 µm pixels, 1/4" CMOS size. 5MP FFC |
| Diameter / Mass |
221 x 126 x 9.2mm, 390 grams |
| Battery |
5197 mAh, 3.8V chemistry (19.75 Whr) |
| OS |
Android 5.1.1 Lollipop |
| Other Connectivity |
2x2 802.11a/b/g/n + BT 4.0, USB2.0, GPS/GLONASS, Mini-HDMI 1.4a |
| Accessories |
SHIELD DirectStylus 2 - $19.99
SHIELD Controller - $59.99
SHIELD Tablet K1 Cover - $39.99 |
| Price |
$199 |
The NVIDIA SHIELD Tablet K1 still has NVIDIA's
Tegra K1 SoC, with four Cortex A15 cores and the incredibly fast single
SMX Kepler GPU. The SoC is paired with 2GB of LPDDR3 RAM and 16GB of
NAND, with the original 32GB model being dropped. There's still microSD
expansion for storing media, and with Android Marshmallow expandable
storage will lose much of its third class status on Android which will
be helpful.
Of course, the biggest change here beyond
the fact that the SHIELD Tablet is being put back on sale is its new
price. At $199 it's $100 cheaper than when it first launched, and it
makes it one of the only good tablets that you can actually get at that
price point with the Nexus 7 having been gone for some time now.
NVIDIA's optional accessories are all available as well, and if you plan
to use the gaming features of the SHIELD Tablet K1 I would definitely
factor the price of the controller into your cost consideration. In any
case, it's good to see the SHIELD Tablet K1 back on sale, and at $199 I
think it's definitely worth considering if you're looking for a tablet
at that price.
Read More ...
AMD Releases Catalyst 15.11.1 Beta Drivers
With
AMD continuing to deliver beta driver updates left and right lately,
today they come to us with another update. Another one of AMD’s point
driver updates, Catalyst 15.11.1 primarily brings performance updates to
some of the headlining tiles of the season, and ups the Display Driver
Version to 15.201.1151.1010.
Overall this driver is a
very straightforward performance driver, with AMD pushing out a batch of
performance optimizations for Star Wars: Battlefront, Fallout 4,
Assassin's Creed Syndicate, and Call of Duty: Black Ops III. Otherwise
there are no bug fixes listed, though AMD does list some known issues,
including that Assassin's Creed Syndicate and Star Wars: Battlefront
cannot launch in full screen mode on some laptops with an Intel CPU and
an AMD GPU.
Meanwhile, it’s worth noting that this is
likely one of the last Catalyst driver releases we’ll see from AMD.
Earlier this month AMD announced their new
Crimson driver branding
and overhaul of their control center, and while AMD has not announced a
specific launch date yet, we do know it’s expected before the end of
the year, only a short 6 weeks away.
Anyhow, as always
those interested in reading more or installing the updated beta drivers
for AMD's desktop, mobile, and integrated GPUs can find them on
AMD's Catalyst beta download page.
Read More ...
NVIDIA Announces Jetson TX1 - A Tegra X1 Module & Development Kit
Although
NVIDIA’s original plans for Tegra haven’t quite panned out as NVIDIA
wanted to – at this point even tablet wins are few and far between – the
company has continued to invest in developing their line of ARM SoCs
and products built around them such as the SHIELD platform. One of the
less public investments NVIDIA has put into Tegra has been on the
development kit side; starting with Tegra K1 in 2014,
NVIDIA began releasing a full development kit for the Tegra platform.
Dubbed Jetson, the TK1 Jetson was a full commercial off the shelf Tegra
system containing the SoC, memory, storage, a Linux distribution
pre-configured for the board, and all of the necessary I/O interfaces a
developer could want. With Jetson NVIDIA was looking to bootstrap the
development of products around Tegra K1 by giving developers the means
to easily prototype their devices around the dev board, before going
into traditional full production.
However since it was a
full COTS implementation of Tegra K1, something unexpected happened for
NVIDIA: developers started using Jetson TK1 outright as a production
board. For small developers doing similarly small product runs, or just
projects that didn’t require a highly integrated solution (e.g. embedded
systems as opposed to mobile devices), some developers would just stick
with Jetson since it meant they could skip system hardware development
and focus on software and/or peripherals.
Moving on to the present, after announcing their latest-generation
Tegra X1 SoC at CES 2015
and integrating it into some of their own products over the past
several months (Drive PX, SHIELD Console, etc) NVIDIA is now rolling out
an updated Jetson product based on the X1. The latest Jetson, which
NVIDIA is appropriately calling the Jetson TX1, is designed to refresh
the platform with the more powerful Tegra X1 SoC and its full ARMv8
AArch64 CPU + Maxwell GPU capabilities. At the same time however, based
on their unexpected success as a COTS product, NVIDIA has redesigned
Jetson to better serve the COTS market while also continuing to serve
the Tegra developer kit market.
The
end result is that for its TX1 iteration Jetson has been split in two,
and now comes as stand-alone compute module with a separate carrier
board for I/O. The Jetson TX1 module itself – which is for all practical
definitions Jetson TX1 in its entirety – contains a full working TX1
system. NVIDIA tells us that Jetson TX1 should offer 2-3 times the
performance of Tegra K1, particularly where the GPU is involved, and
while we don’t have the CPU clockspeed some quick math on NVIDIA’s 1
TFLOPS claim puts the GPU clockspeed at 975MHz (assuming FP16) with the
complete module rated for approximately 10W.
Otherwise
along with the TX1 SoC, NVIDIA has attached 4GB of LPDDR4-3200, a 16GB
eMMC flash module, a 2x2 802.11ac + Bluetooth wireless radio, and a
Gigabit Ethernet controller. By providing a complete TX1 system on a
board a bit smaller than a credit card, NVIDIA is looking to further the
COTS usage of Jetson by giving product developers a smaller dedicated
board specifically designed for COTS usage and quick integration into
shipping products.
Meanwhile
I/O connectivity is now provided by a separate board, be it a
product-specific developer design or the official Jetson TX1 carrier
board, with the Jetson TX1 using a 400 pin board-to-board connector to
attach to other devices. Similar to the original Jetson TK1, the
official Jetson TX1 carrier board is designed to offer TX1 as a
development kit and contains a full suite of I/O including Ethernet,
WiFi + BT antenna connectors, HDMI, USB, M.2, a large number of GPIOs, a
camera serial interface with 5MP camera, and a PCIe 2.0 x4 slot.
Relative to Jetson TK1, the newer TX1 includes more GPIOs, the camera, a
full-size PCIe interface, and it can now work from a more traditional
3.3v power supply.
Moving on, not unlike TX1’s
discrete GPU counterparts,
with the Jetson TX1 platform NVIDIA is strongly focusing on machine
learning and autonomous machines. The company believes that machine
learning is the next great frontier for GPUs – both discrete and
integrated – and is capitalizing on neural net research that has shown
GPUs to be capable of both quickly training and quickly executing neural
nets. This is an important differentiator for NVIDIA given their
strengths in GPU development (both from a tech perspective and overall
SoC GPU performance), and because it is a market that they feel no one
else is truly aiming for (or at least competitive in) at this time. The
Drive PX system already uses TX1 on this basis, and now with Jetson TX1
NVIDIA is looking to extend that relationship to a much wider group of
developers.
Similar
to Jetson TK1 then, Jetson TX1 comes with a suite of software and SDKs
in order to simplify the development process and to give developers a
good starting point for implementing machine learning. Along with the
Linux for Tegra environment, NVIDIA is including their cuDNN neural
network library and VisionWorks computer vision toolkit. Coupled with
other APIs and software packages such as OpenVX and various neural
network systems, NVIDIA is aiming to make the Jetson SDK an ecosystem in
and of itself.
Finally, along with today’s
announcement NVIDIA also unveiled the pricing and availability of the
Jetson TX1 module and the full development kit. NVIDIA will begin taking
pre-orders for the dev kit on the 12
th with kits to start shipping as soon as the 16
th,
and will sell for $599 retail/$299 education. The dev kits will contain
the module, carrier board, camera board, a heatsink-fan for cooling
(which we’re told is grossly overpowered for TX1), and all of the
necessary cables. Meanwhile the stand-alone Jetson TX1 module for use in
commercial products will go on sale in Q1 of 2016, priced at $299 in 1K
quantities.
Read More ...
Qualcomm Snapdragon 820 Experience: HMP Kryo and Demos
While
the Snapdragon 820 has had a number of announcements about various
aspects of the SoC, some details have been mostly left to the
imagination. Today, Qualcomm held an event to release some details about
Snapdragon 820, but also to show off what can be enabled by Snapdragon
820. Some of the main details released today include some estimates of
power, and some additional disclosure on the Kryo CPU cores in
Snapdragon 820.
In
power, Qualcomm published a slide showing average power consumption
using their own internal model for determining days of use. In their
testing, it shows that Snapdragon 820 uses 30% less power for the same
time of use. Of course, this needs to be taken with appropriate
skepticism, but given the use of 14LPP it probably shouldn’t be a
surprise that Snapdragon 820 improves significantly over past devices.
The
other disclosures of note were primarily centered on the CPU and modem.
On the modem side, Qualcomm is claiming 15% improvement in power
efficiency which should eliminate any remaining gap between LTE and WiFi
battery life.
On
the CPU side, while the claims of either doubled performance or power
efficiency have been discussed before, new details on the CPU include
that the quad core CPU is best described as an HMP solution with two
high-performance cores clocked at 2.2 GHz and two low-power cores
clocked at 1.6 or 1.7GHz when looking at previous Qualcomm SoCs with two
clusters that share an architecture. Qualcomm also disclosed that the
CPU architectures of both clusters are identical, but with differences
in cache configuration. However, the differences in cache configuration
weren’t disclosed. I wasn't able to get an answer regarding whether this
is an ARM big.LITTLE design that uses CCI-400 or CCI-500, but given
that there's an L3 cache shared between clusters it's more likely that
this is a completely custom HMP architecture.
In
addition to these disclosures, we saw a number of demos. Probably the
single most interesting demo shown was Sense ID, in which it was shown
that fingerprint sensing worked properly through a sheet of glass and
aluminum. To my recollection both the glass and aluminum were 0.4mm
thick, so the system seems to be relatively robust. For those unfamiliar
with Sense ID, rather than relying of high-resolution capacitive touch
sensing the system uses ultrasonic sound waves to map the fingerprint,
which allows it to penetrate materials like glass and metal and improves
sensitivity despite contaminants like water and dirt.
One
area of note was that Qualcomm is now offering their own speaker
amp/protection IC that would compete with ICs like the NXP TFA9895 that
are quite common in devices today. The WSA8815 chip would also be able
to deliver stereo sound effects in devices with stereo front-facing
speakers. It seems that the primary advantage of this solution is cost
when bundled with the SoC, but it remains to be seen whether OEM
adoption would be widespread.
One
of the other demos was improved low light video and photos by using the
Hexagon 680 DSP and Spectra 14-bit dual ISP. The main area of interest
in this demo was improved visibility of underexposed areas by boosting
shadow visibility, while also eliminating the resulting noise through
temporal noise reduction.
On
the RF side, in addition to showing that the Snapdragon 820 modem is
capable of UE Category 12/13 LTE speeds Qualcomm also demonstrated that
the Snapdragon 820 is capable of dynamically detecting WiFi signal
quality based upon throughput and other metrics that affect VOIP quality
and seamlessly handing off calls from WiFi to LTE and back. We also saw
a demo for Qualcomm’s closed-loop antenna tuning system which allows
for reduced impedance mismatch relative to previous open-loop antenna
tuners which loaded various antenna profiles based upon things like
touch sensing of certain critical areas.
Read More ...
ARM Announces New Cortex-A35 CPU - Ultra-High Efficiency For Wearables & More
Today
as part of the volley of announcements at ARM's TechCon conference we
discover ARM's new low-power application-tier CPU architecture, the
Cortex-A35. ARM follows an interesting product model: The company
chooses to segment its IP offerings into different use-cases depending
on market needs, designing different highly optimized
architectures depending on the target performance and power
requirements. As such, we see the Cortex-A lineup of application
processors categorized in three groups: High performance, high
efficiency, and ultra-high efficiency designs. In the first group we of
course find ARM's big cores such as the Cortex A57 or A72, followed by
the A53 in more efficiency targeted use-cases or in tandem with big
cores in big.LITTLE designs.
What
seems to be counter-intuitive is that ARM sees the A35 not as a
successor to the A53, but rather a replacement for the A7 and A5. During
our in-depth analysis of the Cortex A53 in our
Exynos 5433 review
earlier this year I claimed that the A53 seemed to be more like an
extension to the perf/W curve of the Cortex A7 instead of it being a
part within the same power levels, and now with the A35 ARM seems to
have validated this notion.
As such, the A35 is targeted at power targets below ~125mW where the Cortex A7 and A5 are still very commonly used. T
o give us an idea of what to expect from actual silicon, ARM
shared with us a figure of 90mW at 1GHz on a 28nm manufacturing
process. Of course the A35 will see a wide range of implementations on
different process nodes such as for example 14/16nm or at much higher
clock rates above 2GHz, similar to how we've come to see a wide range of
process and frequency targets for the A53 today.
Most importantly, the A35 now completes ARM's
ARMv8
processor portfolio with designs covering the full range of power and
efficiency targets. The A35 can also be used in conjunction with
A72/A57/A53 cores in big.LITTLE systems, enabling for some very exotic
configurations (A true tri-cluster comes to mind) depending if vendors
see justification in implementing such SoCs.
At
heart, the A35 is still an in-order limited dual-issue architecture
much like the A7 or A53. The 8-stage pipeline depth also hasn't changed
so from this high-level perspective we don't see much difference in
comparison to preceding designs. What ARM has done though is to
improve the individual blocks for better performance and efficiency by having bits and pieces of architectural enhancements that are even newer than what big cores such as the A72 currently employ.
Areas
where the A35 had focused attention on are front-end efficiency
improvements, such as a redesigned instruction fetch unit that improves
branch prediction. The instruction fetch bandwidth was balanced for
power efficiency while the instruction queue is now smaller and also
tuned for efficiency.
It's
especially on memory benchmarks where the A35 will shine compared to
the A7: The A35 adopts a lot of the Cortex A53's memory architecture. On
the L1 memory system of which A35 can have configurable 8 to 64KB of
instruction and data caches we now see use of multi-stream automatic
data prefetching and automatic write stream detection. The L2 memory
system (configurable from 128KB to 1MB) has seen increased buffering
capacity and resource sharing while improving write stream efficiency
and introducting coherency optimizations to reduce contention.
The
NEON/FP pipeline has seen the biggest advancements, besides improved
store performance the new units now add fully pipelined double precision
multiply capability. The pipeline has also seen improvements in terms
of area efficiency, part of the reason enabling the A35 to be smaller
than the A53.
In
terms of power management, the A35 much like the A53 now implements
hardware retention states for both the main CPU core and NEON pipeline
(separate power domains). What seems to be interesting here is that
there is now a hardware governor within the CPU cluster able to
arbitrate automatic entry and exit for retention states. Until now we've
seen very little to no use of retention states by vendors, the only SoC
that I've confirmed to use it was the Snapdragon 810 and that was
subsequently disabled in later software updates in favour of just using
the core power collapse CPU idle state.
At
the same frequency and process, the A35 architecture (codenamed
Mercury), promises to be 10% lower power than the A7 while giving an
6-40% performance uplift depending on use-case. In integer workloads
(SPECint2006) the A35 gives about 6% higher throughput than the A7,
while floating point (SPECfp2000) is supposed to give a more substantial
36% increase.
What is probably more
interesting are apples-to-apples performance and power comparisons to
the A53. Here the A35 actually is extremely intriguing as it is able to
match the A53's performance from 80% to up to 100% depending on
use-case. Browser workloads are where the A35 will trail behind the most
and only be able to provide around 80% of the A53's performance.
Integer workloads are quoted at coming in at 84-85% of the Apollo core,
while as mentioned earlier, memory-heavy workloads are supposed to be on
par with the larger bretheren.
What
puts things in perspective though is that the A35 is able to achieve
all of this at 75% the core size and 68% the power of the A53. ARM
claims that the A35 and A53 may still be used side-by-side and even
envisions big.LITTLE A53.A35 designs, but I have a hard time justifying
continued usage of the A53 because of the cost incentive for vendors to
migrate over to the A35. Even in big.LITTLE with A72 big cores I find it
somewhat hard to see why a vendor would choose to continue to use an
A53 little cluster while they could theoretically just use a higher
clocked A35 to compensate for the performance deficit. Even in the
worst-case scenario where the power advantage would be eliminated by
running a higher frequency, vendors would still be able to gain from the
switch due to the smaller core and subsequent reduced die size.
The A35 is touted as ARM's most configurable processor with
vendors able to alter their designs far beyond simple choices such the
core-count within a cluster. Designers will now also be able
to choose whether they want NEON, Crypto, ACP or even the L2 blocks
included in their implementations. The company envisions this to be
processor for the next billion smartphone users and we'll likely see it
in a very large variety of SoCs powering IoT devices such as wearables
and embedded platforms, to budget smartphones and even high-end ones in
big.LITTLE configurations.
ARM expects first devices with the A35 to ship by the end of 2016. Due to the sheer number of possible applications and expected volume, t
he Cortex A35 will undoubtedly be a very important CPU core for ARM that will be with us for quite some time to come.
Read More ...
ARM Announces ARMv8-M Instruction Set For Microcontrollers – TrustZone Comes to Cortex-M
Kicking
off today in Santa Clara, California is ARM’s annual developer
conference and expo, TechCon. Although ARM announces products
year-round, they always have a couple of announcements reserved for
TechCon and this year is no exception. Being unveiled at 2015’s show is
the
ARM Cortex-A35 CPU and the ARMv8-M instruction set architecture, the latter being the focus of this article.
As
a brief bit of background since we don’t extensively cover ARM’s
microcontroller efforts, in recognition of the unique power and
performance requirements for microcontrollers, ARM produces a separate
instruction set architecture and lineup of CPU cores specifically for
these kinds of products. These are the ARM-M ISAs and the Cortex-M
series of CPUs respectively. The ARM-M ISAs can be thought of as a
cut-down version of ARM’s full ISAs, paring down the features to allow
for simpler CPUs as needed in microcontrollers.
At
this year’s TechCon, ARM is announcing the latest iteration of the
ARM-M ISA, the ARMv8-M ISA. Unlike the full ARMv8 (i.e. ARMv8-A) ISA
that we’re accustomed to seeing implemented in products like ARM’s
Cortex-A57 CPU, Apple’s Twister CPU, and other products, ARM’s focus on
their microcontroller ISA is a bit narrower. Here the focus isn’t on
performance or memory space – factors that led to the expansion to
64-bit CPUs with ARMv8-A AArch64 – but rather on continuing with
microcontroller-suitable 32-bit CPUs while investing in the new features
ARM sees as important over the next half decade or so.
To
that end, ARM’s big focus with ARMv8-M is on security. Key to that is
that ARM’s TrustZone technology is coming to microcontrollers for the
first time.
Previously
only available to ARM-A architecture CPUs, TrustZone is now being
extended to ARM based microcontrollers. And like their bigger siblings,
ARM’s aim here with TrustZone is to lay the groundwork for their
customers to build highly secure devices, for all the benefits and
drawbacks such a device entails. This includes protecting cryptography
engines and certain stored assets (e.g. the secure enclave) against
attack, locking down systems to prevent userland applications from
breaking into the operating system itself, and various degrees of DRM
(one example, as ARM gives is, is firmware IP protection).
ARM
over the last few years has been betting increasingly heavy on
wearables and ioT, so the announcement of ARMv8-M and their focus on
TrustZone is consistent with those bets. ARM microcontrollers are used
in a number of devices as the sole processor, and in more devices still
as a specialized processor working alongside a full ARMv8-A application
processor. So as ARM microcontroller use increasingly expands from
industrial devices and simple black boxes to complex devices that
end-users interact with, there is a need for better security to follow
into these products.
With that said, as
microcontrollers are the lowest of the low power devices in the ARM
ecosystem, ARM had needed to take some care in implementing that
security within the constraints of a microprocessor. Seeking to avoid
compromising response time or efficiency, the ARMv8-M TrustZone retains
the deterministic properties developers need on such devices, so a
TruzeZone interrupt has a low and deterministic latency to the
operation. Similarly, the core of the implementation is based on
switching states rather than hypervisors, avoiding the overhead and
higher resource requirements of the latter.
Of
course like the ARMv8-M ISA itself, TrustZone is an ISA and a model for
just the CPU. To flesh out the full technology ARM is also making a
couple of other ARMv8-M announcements. The first is that the company is
announcing the ARM Advanced Microcontroller Bus Architecture 5 (AMBA 5)
Advanced High-performance Bus 5 (AHB5) specification. The main system
bus for ARM’s microcontrollers, AHB5 goes hand-in-hand with TrustZone to
extend the security model to the rest of the SoC. Through AHB5,
TrustZone microcontroller CPUs can interact with both trusted and
non-trusted devices, including trusted segments of SRAM and flash memory
as required for implementing separated storage.
Also
being announced today is TrustZone CryptoCell, ARM’s implementation of a
TrustZone crypto block, which provides the fixed function hardware
necessary for a full TrustZone implementation. The TrustZone CryptoCell
includes a secure enclave, key generation/provisioning/management, and
the actual fixed function hardware crypto engines.
Ultimately
with today’s ARMv8-M and associated security announcements, ARM is
looking to further flesh out the ARM ecosystem to support full security
at every level and every device from end to end. ARM believes that
developers now need an easier and more standardized way to implement
security on their microcontroller-equipped devices, and this is what
ARMv8-M will provide.
Finally,
and not all that surprising, today’s announcement of the ARMv8-M ISA is
just for the ISA itself, and not for any specific CPUs. ARM has
traditionally announced new Cortex CPU designs separately from the ISA,
and in this case it’s no different. To that end ARM isn’t specifically
talking about when we’ll see ARMv8-M Cortex-M designs announced, but
after today’s announcement it’s safe to say that it’s only a matter of
time.
Read More ...
Google Begins Offline Maps Rollout on Android
Earlier
this year at Google I/O it was announced that Google Maps for Android
and iOS would be receiving an update that would add the ability to save
maps for offline viewing. Interestingly enough, this feature has
actually existed and been removed from Google Maps on more than one
occasion, and so such a prominent announcement gave some hope that it
would stick around for good this time. Today the update is finally
rolling out to Maps users on Android.
The feature works in a fairly straightforward manner.
When searching a location in maps there will now be a download button
in the information page about that location. You can then scroll around
to fit the parts of the map you need into the box shown on screen, and
when you name and save it the maps for that area will be permanently
stored on your device. The applications for this feature are fairly
obvious, such as storing maps of areas where you won't have a cell
signal, or of places you'll be travelling to in other countries where
your phone won't work.
The new version of Google Maps
with offline maps is rolling out now on Android, and an updated version
for iOS will be coming in the near future.
Read More ...
NVIDIA Announces Tesla M40 & M4 Server Cards - Data Center Machine Learning
Slowly
but steadily NVIDIA has been rotating in Maxwell GPUs into the
company’s lineup of Tesla server cards. Though Maxwell is not
well-suited towards the kind of high precision HPC work that the Tesla
lineup was originally crafted for, Maxwell is plenty suitable for just
about every other server use NVIDIA can think of. And as a result the
company has been launching what’s best described as new breeds of
Maxwell cards in the last few months.
After
August’s announcement of the Tesla M60 and M6 cards
– with a focus on VDI and video encoding – NVIDIA is back today for the
announcement of the next set of Tesla cards, the M40 and the M4. In
what the company is dubbing their “hyperscale accelerators,” NVIDIA is
launching these two cards with a focus on capturing a larger portion of
the machine learning market.
| NVIDIA Tesla Family Specification Comparison |
|
Tesla M40 |
Tesla M4 |
Tesla M60 |
Tesla K40 |
| Stream Processors |
3072 |
1024 |
2 x 2048
(4096) |
2880 |
| Boost Clock(s) |
~1140MHz |
~1075MHz |
~1180MHz |
810MHz, 875MHz |
| Memory Clock |
6GHz GDDR5 |
5.5GHz GDDR5 |
5GHz GDDR5 |
6GHz GDDR5 |
| Memory Bus Width |
384-bit |
128-bit |
2 x 256-bit |
384-bit |
| VRAM |
12GB |
4GB |
2 x 8GB
(16GB) |
12GB |
| Single Precision (FP32) |
7 TFLOPS |
2.2 TFLOPS |
9.7 TFLOPS |
4.29 TFLOPS |
| Double Precision (FP64) |
0.21 TFLOPS (1/32) |
0.07 TFLOPS (1/32) |
0.3 TFLOPS (1/32) |
1.43 TFLOPS (1/3) |
| Transistor Count |
8B |
2.94B |
2x 5.2B |
7.1B |
| TDP |
250W |
50W-75W |
225W-300W |
235W |
| Cooling |
Passive |
Passive
(Low Profile) |
Active/Passive |
Active/Passive |
| Manufacturing Process |
TSMC 28nm |
TSMC 28nm |
TSMC 28nm |
TSMC 28nm |
| GPU |
GM200 |
GM206 |
GM204 |
GK110 |
| Target Market |
Machine Learning |
Machine Learning |
VDI |
Compute |
First let’s quickly talk about the cards
themselves. The Tesla M40 marks the introduction of the GM200 GPU to the
Tesla lineup, with NVIDIA looking to put their best single precision
(FP32) GPU to good use. This is a 250 Watt full power and fully enabled
GM200 card – though with Maxwell this distinction loses some meaning –
with NVIDIA outfitting the card with 12GB of GDDR5 VRAM clocked at 6GHz.
We know that Maxwell doesn’t support on-chip ECC for the RAM and
caches, but it’s not clear at this time whether soft-ECC is supported
for the VRAM. Otherwise, with the exception of the change in coolers
this card is a spitting image of the consumer GeForce GTX Titan X.
Joining
the Tesla M40 is the Tesla M4. As hinted at by its single-digit product
number, the M4 is a small, low powered card. In fact this is the first
Tesla card to be released in a PCIe half-height low profile form factor,
with NVIDIA specifically aiming for dense clusters of these cards.
Tesla M4 is based on GM206 – this being the GPU’s first use in a Tesla
product as well – and is paired with 4GB of GDDR5 clocked at 5GHz.
NVIDIA offers multiple power/performance configurations of the M4
depending on server owner’s needs, ranging from 50W to 75W, with the
highest power mode rated to deliver up to 2.2TFLOPS of FP32 performance.
Both
the Tesla M40 and M4 are being pitched at the machine learning market,
which has been a strong focus for NVIDIA since the very start of the
year. The company believes that machine learning is the next great
frontier for GPUs, capitalizing on neural net research that has shown
GPUs to be capable of both quickly training and quickly executing neural
nets. Neural nets in turn are increasingly being used as more efficient
means for companies to process vast amounts of audio & video
data (e.g. the Facebooks of the world).
To that end we have seen the company focus on machine learning in the automotive sector with products such as the
Drive PX system and lay out their long-term plans for machine learning with the forthcoming Pascal architecture at
GTC 2015.
In the interim then we have the Tesla M40 and Tesla M4 for building
machine learning setups with NVIDIA’s current-generation architecture.
Given
their performance and power profiles, Tesla M40 and M4 are intended to
split the machine learning market on the basis of training versus
execution The powerful M40 being well-suited for quicker training of
neural nets and other systems, while the more compact M4 is well-suited
for dense clusters of systems actually executing various machine
learning tasks. Note that it’s interesting that NVIDIA is pitching the
M40 and not the more powerful M60 for training tasks; as NVIDIA briefly
discussed among their long-term plans at GTC 2015, current training
algorithms don’t scale very well beyond a couple of GPUs, so users are
better off with a couple top-tier GM200 GPUs than a larger array of
densely packed GM204 GPUs. As a result the M40 occupies an interesting
position as the company’s top Tesla card for machine learning tasks that
aren’t trivially scalable to many GPUs.
Meanwhile,
along with today’s hardware announcement NVIDIA is also announcing a
new software suite to tie together their hyperscale ambitions. Dubbed
the “NVIDIA Hyperscale Suite,” the company is putting together software
targeted at end-user facing web services. Arguably the lynchpin of the
suite is NVIDIA’s GPU REST Engine, a service for
RESTful APIs
to utilize the GPU, and in turn allowing web services to easily access
GPU resources. NVIDIA anticipates the GPU REST Engine enabling
everything from search acceleration to image classification, and to
start things off they are providing the NVIDIA Image Compute Engine, a
REST-capable service for GPU image resizing. Meanwhile the company is
also be providing their cuDNN neural net software as part of the suite,
and versions of FFmpeg with support for NVIDIA’s hardware video encode
and decode blocks to speed up video processing and transcoding.
Wrapping
things up, as is common with Tesla product releases, today’s
announcements will predate the hardware itself by a bit. NVIDIA tells us
that the Tesla M40 and the hyperscale software suite will be available
later this year (with just over a month and a half remaining). Meanwhile
the Tesla M4 will be released in Q1 of 2016. NVIDIA has not announced
card pricing at this time.
Read More ...
The Microsoft Surface Book Review
Microsoft
has released what they are calling "The Ultimate Laptop" and with their
first attempt at moving outside the tablet segment, we take a look at
the new Surface Book and how it compares. Competition in the notebook
segment is much more intense than the high end tablet market, and
Microsoft is aiming for the top.
Read More ...
Imagination Announces New P6600, M6200, M6250 Warrior CPUs
Today
Imagination launches three new MIPS processor IPs: One in the
performance category of Warrior CPUs, the P6600 and two embedded M-class
core, the M6200 and M6250.
Warrior P6600
Starting
off with the P6600, this is Imagination's new MIPS flagship core
succeeding the P5600. The P5600 was a 3-wide out-of-order design with a
pipeline depth of up to 16 stages. The P6600 keeps most of the
predecessor's characteristics such as the main architectural features
or full hardware virtualization and security through
OmniShield, but adds compatibility for MIPS64 64-bit processing on top. Imagination
first introduced
a mobile oritented 64-bit MIPS CPU back with the I6400 a little more
than a year ago but we've yet to see vendors announce products with it.
We're
still lacking any details on the architectural improvements of the
P6600 over the P5600 so it seems that for now we're left with guessing
what kind of performance the new core will bring. The P5600 was directly
competing with ARM's Cortex A15 in terms of IPC, but ARM has since then
not only announced but also seen silicon with two successor IPs to the
A15 (A57 and A72), so the P6600 will have some tough competition ahead
of itself once it arrives in products.
The
P6600, much like the P5600 can be implemented from single-core to
six-core cluster configurations. What is interesting that as opposed to
ARM CPU IP, the MIPS cores allow for asynchronous clock planes between
the individual cores if the vendors wishes to implement the SoC's power
management in this way (It can also be set up to work in a synchronous
way).
"MIPS P6600 is the next evolution
of the high-end MIPS P-class family and builds on the 32-bit P5600 CPU.
P6600 is a balanced CPU for mainstream/high-performance computing,
enabling powerful multicore 64-bit SoCs with optimal area efficiency for
applications in segments including mobile, home entertainment,
networking, automotive, HPC or servers, and more. Customers have already
licensed the P6600 for applications including high-performance
computing and advanced image and vision systems."
Warrior M6200 & M6250
Also
as part of today's announcement we see two new embedded CPU cores, the
M6200 and M6250. Both cores are successors to the microAptiv-UP and UC
but able to run at up to 30% higher frequency. The new processors also
see an ISA upgrade to MIPS32 Release 6 instead of Release 5.
The
M6200 is targeted at real-time embedded operating systems with minimal
funtionality for cost- and power-savings. It has no MMU and as such can
only be described as a microcontroller part.
The
M6250 is the bigger brother of the M6200 and the biggest difference is
the inclusion of a memory management unit (MMU) that makes this a full
fledged processor core that can run operating systems like Linux.
"M6200
and M6250 are configurable and fully synthesizable solutions for
devices requiring a high level of performance efficiency and small
silicon area including wireless or wired modems, GPU supervisors, flash
and SSD controllers, industrial and motor control, advanced audio and
more."
Read More ...
Intel's Xeon D Product Family Updated with Storage and Networking-Specific SKUs
Intel's
Xeon D
has been one of the most exciting platforms to come out of Intel this
year. Xeon D has created more excitement in the micro-server / edge
server market compared to the introduction of Avoton and Rangeley (based
on Silvermont x86 Atom cores) a few years back. In introducing the 22nm
Atom-based server SoCs, Intel clearly delineated different SKUs for
different market segments. While Avoton (C2xx0) concentrated on the
storage server market, Rangeley (C2xx8) added some communication
accelerators that made it a good fit for networking and communication
applications.
Xeon D was launched with two SKUs (D1520,
a 4C/8T SiP, and the D1540, a 8C/16T SiP) earlier this year. While
those two SKUs covered the web hosting applications, today's launches
cover the storage and edge network applications. Intel's slide from a
presentation made earlier today sums up the various products in the
lineup. Eight new Xeons and three new Pentium processors are being
launched in the D-1500 lineup and they come in both 45W and 35W TDP
versions. Interestingly, Intel indicated that 12-core and 16-core Xeon D
SiPs can be expected early next year.
Note:
The Pentium D Processors indicated in the above slide were not launched
despite being part of the slide set. Currently, there are a total of 10 Xeon-D SKUs (as of Q4 2015).
Patrick at ServeTheHome has a
nice graphic
summarizing the clock speeds and pricing of these products. The D15x1
SKUs target the storage market, while the D15x7 and D15x8 target the
networking / communication segments.
Intel claims that the new storage SKUs provide as much as 6x the performance of the high-end Avoton-based platforms.
Intel's
Storage Acceleration Library (ISA-L) provides accelerators for
compression, checksumming, parity calculation and cryptograhic functions
(encryption as well as hashing).
The
Storage Performance Development Kit (SPDK) provides better optimization
compared to the native Linux drivers - particularly as the number of
storage devices in the system ramps up.
On
the networking front, Intel claims up to 5.4x higher performance
compared to the Rangeley-based platforms. Intel is promoting their Data
Plane Development Kit (DPDK) to achieve better performance for L3
packet forwarding, VM packet forwarding with Open vSwitch, and IPSec
forwarding (VPN applications).
ServeTheHome
talks
about how the communication accelerators have gained extensive software
support since they were launched with the Rangeley SoCs in 2013.
One
of the disappointing aspects with respect to the D1520 and D1540 (at
least for those intending to use them as virtualization hosts) was the
pulling back of the advertised SR-IOV feature. It remains to be seen if the new SKUs have the feature enabled.
In addition to the new Xeon D SKUs, Intel also announced the
FM10000 Ethernet multi-host controller family
that can provide up to 36 Ethernet lanes. The FM10000 family supports
1Gbps, 2.5Gbps, 10Gbps, and 25Gbps Ethernet ports and the ability to
group four lanes as 40Gbps or 100Gbps ports. The integrated Ethernet
controllers can be configured as four 50Gbps or eight 25Gbps host
interfaces,.
The new
X550 single-chip, low-cost 10GbE platform was also launched. It supports NBASE-T technology (for 2.5Gbps as well as 5 Gbps operation, in addition to 10Gbps).
Operating
via a PCIe 3.0 x1 / x4 / x8 link, the new 10GBASE-T controller
integrates both MAC and PHY in a single package, and comes in both
single and dual-port varieties. Power consumption is just 11 W with both
10GbE ports active, making it amenable to passive heatsink thermal
solutions.
Read More ...
TAG Heuer Unveils The Intel-Powered Connected Smartwatch
Today
TAG Heuer, a traditional Swiss watchmaker, announced their entry into
the world of smartwatches with the TAG Heuer Connected. This is really
the first example of a luxury Android wear watch, and also the first
example of a traditional mechanical watch manufacturer moving into the
smartwatch space.
The TAG Heuer Connected has a
diameter of 46mm, a thickness of 12.8mm, and a mass of 52 grams. The
chassis of the watch is made of titanium, and the LCD display is covered
by a sheet of sapphire glass. The display itself is a 1.5" 360x360
fully circular transflective LTPS LCD, which means it can use the
reflection of light to improve visibility and drive down power
consumption. The last time I remember hearing about these sorts of
displays was Pixel Qi's transflective LCDs, but the tech hasn't really
gone anywhere since that time. It'll be interesting to see who is making
the panel for the TAG Heuer Connected and how it fares in bright light
compared to other smartwatches, as well as compared to a traditional
mechanical watch which doesn't use an LCD at all.
|
TAG Heuer Connected |
| SoC |
Intel Atom Z34xx |
| RAM |
1GB |
| NAND |
4GB |
| Display |
1.5" 360x360 LCD, 240ppi |
| Diameter / Mass |
46mm / 52g |
| Battery |
410mAh |
| OS |
Android Wear |
| Other Connectivity |
802.11b/g/n + BT 4.1 |
| Price |
$1499 |
Interestingly, the TAG Heuer connect is powered by
an Intel SoC rather than the Snapdragon 400 chip that has shown up in
most Android Wear devices. More specifically, it's an Intel Z34xx
series SoC, which has a peak frequency of 1.6GHz but TAG Heuer notes
that the nominal frequency will be more like 500MHz. The SoC is paired
with 1GB of RAM and 4GB of NAND, which puts it ahead of the 512MB of RAM
found in most Android Wear watches. The sensors include an
accelerometer and a gyroscope, but no heart rate monitor which is
definitely a letdown for fitness-oriented buyers. The watch is also
advertised as having IP67 water resistance.
Because 30%
of the Connected's parts are made outside of Switzerland the watch
isn't officially "Swiss made", and I don't expect that's going to be an
easy problem to overcome when there are now many electrical parts inside
the watch being made overseas. Something interesting is that the
Connected is modeled off of TAG Heuer's Carrera mechanical watch, and
after two years the company will allow you to trade in your Connected
along with $1500 to receive an actual Carrera. To me that move seems a
bit pessimistic about the company's own future in the smartwatch space,
as it seems like there's an assumption that users will give up a
smartwatch and go back to owning a mechanical watch. It would make more
sense to me if you could trade up to newer versions of the Connected.
The
last, and possibly most important detail about the TAG Heuer Connected
is the price. TAG Heuer's mechanical watches can cost several hundred
dollars, and so it's no surprise that the TAG Heuer Connected will have a
retail price of $1500
Read More ...
The Google Nexus 5X Review
Google's
first hardware collaboration with LG brought us the Nexus 4. Like the
Nexus 7, the Nexus 4 followed a philosophy of bringing as much power and
quality as possible to a reasonably affordable price point. The Nexus 4
definitely wasn't a perfect phone, but it was certainly good relative
to its price, and it showed that a phone can still be good even if it
doesn't cost $600. About one year later Google and LG collaborated again
to bring us the Nexus 5, a device which I and many other users fondly
remember as an affordable phone that actually brought many of the
specifications you would expect to see in a device that costed
significantly more.
While I'm sure many hoped that 2014
would bring the next iteration of an LG Nexus device, it wasn't meant
to be. Instead we got the Nexus 6 made by Motorola, which didn't really
follow the pricing philosophy of the LG Nexus devices, and wasn't very
competitive with devices like the Galaxy Note 4 despite its equivalent
cost. At that point the future of affordable Nexus devices was unclear,
and I wasn't even sure if we'd see a true successor to the Nexus 5.
Fortunately, this year is the year that LG returns to bring us the next
iteration of their Nexus phones, with the new device appropriately being
named the Nexus 5X. Read on for the full review, and find out if the
Nexus 5X is a worthy successor to the Nexus 5.
Read More ...
Examining Intel's New Speed Shift Tech on Skylake: More Responsive Processors
Modern
computer processors are constantly changing their operating frequency
(and voltage) depending on workload. For Intel processors, this is often
handled by the operating system which will request a particular level
of performance, known as the Performance State or P-State, from the
processor. The processor then adjusts its frequencies and voltage levels
to accomodate, in a DVFS (dynamic voltage and frequency scaling) sort
of way, but only at the P-states fixed at the time of production. While
the best for performance would be to run the system at the maximum all
the time, due to the high voltage, this is the least efficient way to
run a processor and wasteful in terms of energy used, which for mobile
devices means a shorter battery life or thermal throttling. With the
P-state model, to increase efficiency, the operating system can request
lower P-states in order to save power, but if a task requires more
performance, and the power/thermal budgets are sufficient, the P-State
can be changed to accomodate. This 'technology' on Intel processors has
historically been called 'Speed Step'.
With Skylake, Intel's newest 6th generation Core processors, this
changes. The processor has been designed in a way that with the right
commands, the OS can hand control of the frequency and voltage back
to the processor. Intel is calling this technology 'Speed Shift'. We’ve
discussed Speed Shift before in Ian’s
Skylake architecture analysis,
but despite the in-depth talk from Intel, Speed Shift was noticably
absent at the time of the launch of the processors. This is due to one
of the requirements for Speed Shift - it requires operating system
support to be able to hand over control of the processor performance to
the CPU, and Intel had to work with Microsoft in order to get this
functionality enabled in Windows 10. As of right now, anyone with a
Skylake processor is actually not getting the benefit of the technology,
at least right now. A patch will be rolled out in November for Windows
10 which will enable this functionality, but it is worth noting that it
will take a while for it to roll out to new Windows 10 purchases.
Compared
to Speed Step / P-state transitions, Intel's new Speed Shift
terminology, changes the game by having the operating system relinquish
some or all control of the P-States, and handing that control off to the
processor. This has a couple of noticable benefits. First, it is much
faster for the processor to control the ramp up and down in frequency,
compared to OS control. Second, the processor has much finer control
over its states, allowing it to choose the most optimum performance
level for a given task, and therefore using less energy as a result.
Specific jumps in frequency are reduced to around 1ms with Speed Shift's CPU control from 20-30 ms on OS control, and going from an efficient power
state to maximum performance can be done in around 35 ms, compared to
around 100 ms with the legacy implementation. As seen in the images
below, neither technology can jump from low to high instantly, because to maintain data coherency through frequency/voltage changes there is an element of gradient as data is realigned.
The
ability to quickly ramp up performance is done to increase overall
responsiveness of the system, rather than linger at lower frequencies
waiting for OS to pass commands through a translation layer. Speed Shift
cannot increase absolute maximum performance, but on short workloads
that require a brief burst of performance, it can make a big difference
in how quickly that task gets done. Ultimately, much of what we do falls
more into this category, such as web browsing or office work. As an
example, web browsing is all about getting the page loaded quickly, and
then getting the processor back down to idle.
For
this short piece, Intel was able to provide us with the Windows
10 patch for Speed Shift ahead of time, so that we could test and see
what kind of gains it can achieve. This gives us a somewhat unique
situation, since we can isolate this one variable on a new processor and
measure its impact on various workloads.
To test Speed
Shift, I’ve chosen several tasks which have workloads that could show
some gain from Speed Shift. Tests which run the processor at its maximum
frequency for long periods of time are not going to show any
significant gain, since you are not limited by the responsiveness of the
processor in those cases. The first test is PCMark 8, which is a
benchmark which attempts to represent real-life tasks, and the workload
is not constant. In addition, I’ve run the system through several
Javascript tests, which are the best case scenario for something like
Speed Shift, since the processor has to quickly complete a task in order
to allow you to enjoy a website.
The processor in
question is an Intel Core i7-6600U, with a base frequency of 2.6 GHz,
and turbo frequency of 3.4 GHz. Despite the base frequency being rated
on the box at 2.6 GHz, the processor can go all the way down to 400 Mhz
when idle, so being able to ramp up quickly could make a big impact even
on the U-series Skylake processors. My guess is that it will be even
more beneficial to the Y series Core m3/m5/m7 parts since they have a
larger dynamic range, and typically more thermal constraints.
PCMark 8
Both
the Home and Work tests show a very small gain with Speed Shift
enabled. The length of these benchmarks, which are between 30 and 50
minutes, would likely mask any gains on short workloads. I think this
illustrates that Speed Shift is just one more tool, and not a holy grail
for performance. The gain on Home is just under 3%, and the difference
on the Work test is negligible.
JavaScript Tests
JavaScript
is one of the use cases where short burst workloads are the name of the
game, and here Speed Shift has a much bigger impact. All tests were
done with the Microsoft Edge browser.
The
time to complete the Kraken 1.1 test is the least affected, with just a
2.6% performance gain, but Octane's scores shows over a 4% increase.
The big win here though is WebXPRT. WebXPRT includes subtests, and in
particular the Photo Enhancement subtest can see up to a 50% improvement
in performance. This bumps the scores up significantly, with WebXPRT
2015 showing an almost 20% score increase, and WebXPRT 2013 has a 26%
gain. These leaps in performance are certainly the kind that would be
noticeable to the end user manipulating photographs in something like
Picasa or watching web-page based graph adjustments such as live stock
feeds.
Power Consumption
The other
side of the coin is power consumption. Having a processor that can
quickly ramp up to its maximum frequency could mean that it will consume
more power due to the greater penalty of increasing the voltage, but if
it can complete the task quickly and get back to idle again, there is a
chance to be more efficient when work is done in 10s of milliseconds
rather than 100s of milliseconds, as the frequency ramps up and down
again before the old P-state method has decided to do anything. The
principle of 'work fast, finish now' was the backbone of Intel's 'Race
To Sleep' strategy during the ultrabook era and focused on the impulse
of response-related performance, however the drive for battery life
means that efficiency has tended to matter more, especially as devices
and batteries get smaller.
Due to the way
modern processors work, we
don’t have the tools to directly measure the SoC power. Intel has told
us that Speed Shift does not impact battery life very much, one way or
the other, so to verify this, I've run our light battery life test with
the option disabled and enabled.
This
task is likely one of the best case scenarios for Speed Shift. It
consists of launching four web pages per minute, with plenty of idle
time in between. Although Speed Shift seems to have a slight edge, it is
very small and would fall within the margin of error on this test. Some
tasks may see a slight improvement in efficiency, and others may see a
slight regression, but Speed Shift is less of a power savings tool than
other pieces of Skylake. Looking at it another way, if, for example, the
XPS 13 with Skylake was to get 15 hours of battery life, Speed Shift
would only change the result by about 7 minutes. Responsiveness
increases, but net power use remains about the same.
Final Words
With
Skylake, while there was not the large leap in clock for clock
performance gain that we have become accustomed to with new Intel
microarchitectures, but when you look at the overall package, there was a
decent net gain in performance combined with new technologies. For
example, being able to maintain higher Turbo frequencies on multiple
cores has increased the stock to stock performance more than the smaller
IPC gains.
Speed Shift is just one small part of the
overall performance gain, and one that we have not been able to look at
until now. It does lead to some pretty big gains in task completion, if
the workloads are bursty and short enough for it to make a difference.
It can’t increase the absolute performance of the processor, but it can
get it to maximum performance in a much shorter amount of time, as well
as get it back down to idle quicker. Intel is billing it as improved
responsiveness, and it’s pretty clear that they have achieved that.
The
one missing link is operating system support. We’ve been told that the
patch to enable this is coming to Windows 10 in November. While this
short piece looks at what Speed Shift can bring to the table in terms of
performance, if you'd like to read more about how it is implemented,
please check out the
Skylake architecture analysis which goes into more detail.
Update: Daniel Rubino at
Windows Central
has tested the latest Windows 10 Insider build 10586 and it appears to
enable Speed Shift on his Surface Pro 4, which is in-line with the
November timeline we were provided.
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