gpu News - Page 16 of 30 - CNX Software

February 8, 2018 by Jean-Luc Aufranc (CNXSoft) - 15 Comments

T-bao Tbook X8S Pro Apollo Lake Laptop is Equipped with an NVIDIA Geforce GPU

Most products based on Intel Apollo Lake processor do so to leverage the low cost and low power of the chip that also embeds Intel HD graphics removing the need for an external graphics card. But T-bao Tbook X8S Pro laptop powered by Intel Celeron J3455 Apollo Lake “Desktop” processor also comes with an NVIDIA GeForce 920M GPU which should boost graphics performance. Tbook X8S Pro specifications: SoC – Intel Celeron J3455 quad core Apollo Lake processor @ 1.50 / 2.30 GHz with (unused) 12EU Intel HD Graphics 500; 10W TDP GPU – NVIDIA GeForce 920M @ 954 MHz with 2GB RAM System Memory – 6GB DDR3 Storage – 128GB eMMC flash or M.2 SSD (unclear), micro SD card slot up to 128 GB Display – 15.6″ IPS screen with 1920×1080 resolution Video Output – HDMI output Audio – Built-in microphone, and stereo speakers; 3.5mm audio jack Connectivity – Gigabit […]

January 26, 2018 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Imagination PowerVR Series8XT GT8540 GPU Can Drive up to Six 4K Screens, Supports Hardware Virtualization

Imagination Technologies introduces PowerVR Furian architecture last year with improved performance, power and density, as well as dual cluster PowerVR Series8XT GT8525 GPU based on the new architecture, and targeting high-end smartphones, virtual reality and automotive products. The company has now introduced a quad cluster Furian GPU called PowerVR Series8XT GT8540 that can simultaneously drive up to six 4K screens at 60fps thanks to an 80% fillrate density improvement, and supports virtualization providing separation of services and applications. The new GPU mostly targets the automotive market with some new cars now requiring multiple screen support with high resolution displays for cluster, Head-Up Display (HUD) and infotainment. Hardware virtualization is equally important for automotive application, as you’ll want to separate safety-critical code, from infotainment applications for example, so if the latter crashes, the safety-critical code can still run unhindered. Each would run on separate shaders processing unit, with up to 8 […]

September 26, 2017September 26, 2017 by Jean-Luc Aufranc (CNXSoft) - 23 Comments

Allwinner SoCs with Mali GPU Get Mainline Linux OpenGL ES Support

OpenGL ES support in Linux for ARM SoC is usually pretty hard to get because of closed source binary blobs coupled with the manufacturers focus on Android. Workarounds include open driver projects such as Freedreno for Qualcomm Adreno GPU, Nouveau for Tegra, or Etnaviv for Vivante GPUs, as well as libhybris library that converts Linux calls into Android calls in order to leverage existing Android GPU binary blobs. Allwinner processors relies on either PoverVR or ARM Mali GPU, and the former does not have any open source project, while some work is still being going for the latter with Lima project, but it’s not ready yet. That means so far, you’re only option was to use libhybris for either GPU family. The good news is that Free Electrons engineers have been working on OpenGL ES support for ARM Mali GPU for Allwinner processor, and have been allowed to release the […]

September 21, 2017November 24, 2022 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Imagination Announces PowerVR Series2NX Neural Network Accelerator (NNA), and PowerVR Series9XE and 9XM GPUs

Imagination Technologies has just made two announcements: one for their PowerVR Series2NX neural network accelerator, and the other for the new high-end GPU families: PowerVR Series9XE and 9XM. PowerVR Series2NX neural network accelerator The companies claims 2NX can deliver twice the performance and half the bandwidth of nearest competitor, and it’s the first dedicated hardware solution with flexible bit-depth support from 16-bit down to 4-bit. Key benefits of their solution (based on market data available in August 2017 from a variety of sources) include: Highest inference/mW IP cores to deliver the lowest power consumption Highest inference/mm2 IP cores to enable the most cost-effective solutions Lowest bandwidth solution with support for fully flexible bit depth for weights and data including low bandwidth modes down to 4-bit 2048 MACs/cycle in a single core, with the ability to go to higher levels with multi core The PowerVR 2NX NNA is expected to be […]

August 9, 2017August 9, 2017 by Jean-Luc Aufranc (CNXSoft) - 16 Comments

Movidius Neural Compute Stick Shown to Boost Deep Learning Performance by about 3 Times on Raspberry Pi 3 Board

Intel recently launched Movidius Neural Compute Stick (MvNCS)for low power USB based deep learning applications such as object recognition, and after some initial confusions, we could confirm the Neural stick could also be used on ARM based platforms such as the Raspberry Pi 3. Kochi Nakamura, who wrote the code for GPU accelerated object recognition on the Raspberry Pi 3 board, got hold of one sample in order to compare the performance between GPU and MvNCS acceleration. His first attempt was quite confusing as with GoogLeNet, Raspberry Pi 3 + MvNCS achieved an average inference time of about 560ms, against 320 ms while using VideoCore IV GPU in RPi3 board. But then it was discovered that the “stream_infer.py” demo would only use one core out of the 12 VLIW 128-bit vector SHAVE processors in Intel’s Movidius Myriad 2 VPU, and after enabling all those 12 cores instead of just one, […]

August 8, 2017August 21, 2022 by Jean-Luc Aufranc (CNXSoft) - 30 Comments

Work on VideoCore V GPU Drivers Could Pave the Way for Raspberry Pi 4 Board

I’ve come across an article on Phoronix this morning, about VideoCore IV GPU used in Broadcom BCM283x “Raspberry Pi” processors, but part of the post also mentioned work related to VC5 drivers for the next generation VideoCore V GPU, written by Eric Anholt, working for Broadcom, and in charge of the open source code related to VideoCore IV GPU for Raspberry Pi. This led me Eric’s blog “This Week in VC4/VC5” and articles such as “2017-07-10: vc5, raspbian performance“, where he explains he committed Mesa drivers for VC5. I’ve just pushed a “vc5” branch to my Mesa tree (https://github.com/anholt/mesa/commits/vc5). This is the culmination of a couple of months of work on building a new driver for Broadcom’s V3D 3.3. V3D 3.3 is a GLES3.1 part, though I’m nowhere near conformance yet. This driver is for BCM7268, a set-top-box SOC that boots an upstream Linux kernel. I’m really excited to be […]

June 13, 2017 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Android Can Now Boot with a Full Open Source Graphics Stack on NXP i.MX6 Boards

While the Android operating systems is itself open source, it still relies on proprietary binary files to leverage GPU acceleration, VPU hardware decoding, wireless connectivity, and so on. It’s been possible to run Android with an open source software graphics stack, but it’s normally terribly slow and barely usable. But Collabora has announced it could now boot Android with a full-graphics stack on iMX6 platforms using no proprietary blobs at all. To do so, they leveraged the work done on Etnaviv open source drivers for Vivante GPUs, and adding the different formats used for graphical buffers in Android and Mesa library using modifiers representing different properties of buffers. They further explain: Support was added in two places; Mesa and gbm_gralloc. Mesa has had support added to many of the buffer allocation functions and to GBM (which is the API provided by Mesa, that gbm_gralloc uses). gbm_gralloc in turn had support […]

May 27, 2017April 12, 2019 by Jean-Luc Aufranc (CNXSoft) - 23 Comments

ARM Cortex-A75 & Cortex-A55 Cores, and Mali-G72 GPU Details Revealed

We’ve already seen ARM Cortex A75 cores were coming thanks to leak showing Snapdragon 845 SoC will feature custom Cortex A75 cores, but we did not have many details. But since we live in a world where “to leak is glorious”, we already have some slides originally leaked through VideoCardz with the post now deleted, but Liliputing & TheAndroidSoul got some of the slides before deletion, so let’s see what we’ve got here. ARM Cortex A75 So ARM Cortex-A75 will be about 20% faster than Cortex A73 for single thread operation, itself already 30% faster than Cortex A72. It will also be the first DynamIQ capable processor together with Cortex A55 with both cores potentially used in big.LITTLE configuration. Cortex A75 performance is only better for peak performance, and remain the same as Cortex-A73 for sustained performance. The chart above does not start at zero, so it appear as though […]