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May 5, 2021May 5, 2021 by Jean-Luc Aufranc (CNXSoft) - 10 Comments

SigmaStar SSC33x Camera SoCs are pin-to-pin compatible with Hisilicon Hi3516/Hi3518 processors

We’ve been writing a fair amount of posts about SigmaStar SSD201/SSD202D processors for smart displays in recent times. But the company also has various camera SoC’s with SSC333, SSC335, SSC336, SSC337, SS338, and SSC339 parts. Those processors feature one or two Cortex-A7 core, embedded RAM, as well as an optional AI accelerator called DLA (Deep Learning Accelerator). The chips manufactured using a 28nm or 22nm process, with the latter being used for parts with the AI accelerator. Most of the Sigmastar SCC33x processors also happen to be pin-to-pin compatible with HiSilicon Hi3516 or Hi3518 SoC that are found in a wide range of IP cameras. Let’s take SSC336D/SSC336Q processor as an example since it comes with the AI accelerator and we have a datasheet courtesy of linux-chenxing.com. SigmaStar SSC336D/SSC336Q camera SoC key features & specifications: CPU – Dual-core Arm Cortex-A7 processor @ 1 GHz with Neon and FPU Embedded Memory […]

May 5, 2021 by Jean-Luc Aufranc (CNXSoft) - No Comments

Imago “VisionAI” Smart AI Camera supports Tensorflow Lite & AutoML Vision Edge

Imago Technologies GmbH “VisionAI” is a programmable Smart AI camera that combines a quad-core Cortex-A53 processor @ 1.8 GHz together with Google Edge TPU, and designed for embedded image processing applications in the fields of AI, Deep Learning, and Machine Learning. The smart camera supports TensorFlow Lite and AutoML Vision Edge frameworks, and is suited for tasks such as pattern recognition, classification, anomaly or defect detection in inspection applications, code reading, and other machine vision applications. Imago VisionAI (VisionSensor PV3 AI) camera specifications: SoC – Unnamed quad-core Arm Cortex-A53 processor @ 1.8 GHz (likely NXP i.MX 8M Mini) AI Accelerator – Google Edge TPU with up to 4 TOPS of AI processing power System Memory – 2 GB DDR4 RAM Storage – MicroSD card up to 32GB Connectivity – Gigabit Ethernet M12 connector Camera 1/1.8” 5MP mono or color CMOS sensor with 2560 × 1936 pixels resolution, up to 65 […]

April 29, 2021April 29, 2021 by Jean-Luc Aufranc (CNXSoft) - 9 Comments

Allwinner V831 NPU (Neural Processor Unit) reverse-engineered

When Sipeed introduced MAIX-II Dock AIoT vision development kit, they asked help from the community to help reverse-engineer Allwinner V831‘s NPU in order to make an open-source AI toolchain based on NCNN. Sipeed already had decoded the NPU registers, and Jasbir offered help for the next step and received a free sample board to try it out. Good progress has been made and it’s now possible to detect objects like a boat using cifar10 object recognition sample. Allwinner V831’s NPU is based on a customized implementation of NVIDIA Deep Learning Accelerator (NVDLA) open-source architecture, something that Allwinner (through Sipeed) asked us to remove from the initial announcement, and after reverse-engineering work, Jasbir determined the following key finding: The NPU clock defaults to 400 MHz, but can be set between 100 and 1200 MHz NPU is implemented with nv_small configuration (NV Small Model), and relies on shared system memory for all […]

April 29, 2021April 30, 2021 by Jean-Luc Aufranc (CNXSoft) - 25 Comments

Allwinner Processor 2021-2022 Roadmap – Allwinner T827, T723 and T1033 SoC’s

Last year, we published the Allwinner A-series processor roadmap for 2020-2021 with notably Allwinner A33E, A100, and A200 SoCs. Allwinner A100 was supposed to be released in 2019, but a search on Aliexpress showed exactly zero matches. We did write about Allwinner A100 mainline Linux support a little while ago, and today, I eventually found one Allwinner A100 tablet with the $60 Hyundai HyTab 7WC1. I had no better luck in my search for Allwinner A33E and A200 platforms. But I also got lucky today with another Allwinner roadmap for 2021-2022 with some very interesting new processors, provided they happen. A look at 2020 processors But let’s look at the year 2020 first. We already have most details about Allwinner A133 quad-core Cortex-A53 processor, which is also called T509 apparently following the merging of the Allwinner A-Series business unit, focusing on tablets, into the Allwinner T-Series for industrial & automotive […]

April 28, 2021April 28, 2021 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Xilinx Introduces Kria K26 SoM and vision AI devkit based on Zynq Ultrascale+ XCK26 FPGA MPSoC

Silicon vendors will usually focus on chip design, and provide an expensive evaluation kit to early customers, leaving the design of cost-optimized boards and system-on-modules to embedded systems companies. But Xilinx has decided to enter the latter market with the Kria portfolio of adaptive system-on-modules (SOMs) and production-ready small form factor embedded boards starting with Kria K26 SoM powered by Zynq UltraScale+ XCK26 FPGA MPSoC with a quad-core Arm Cortex-A53 processor, up to 250 thousand logic cells, and a H.264/265 video codec designed for Edge AI applications, as well as computer vision development kit. Kria K26 System-on-Module Kria K26 module specifications: MPSoC – Xilinx Zynq Ultrascale+ custom-built XCK26 with quad-core Arm Cortex-A53 processor up to 1.5GHz, dual-core Arm Cortex-R5F real-time processor up to 600MHz, Mali-400 MP2 GPU up to 667MHz, 4Kp60 VPU, 26.6Mb On-Chip SRAM, 256K logic cells, 1,248 DSP slices System Memory – 4GB 64-bit DDR4 (non-ECC) Storage – […]

April 27, 2021April 27, 2021 by Jean-Luc Aufranc (CNXSoft) - 7 Comments

SiFive Intelligence X280 64-bit RISC-V processor integrates AI extensions

The last RISC-V core announced by SiFive was the U8-Series out-of-order RISC-V Core IP that aims to compete against Arm Cortex-A72 Core. But in their latest announcement, the company built upon the 64-bit RISC-V U7-series with the SiFive Intelligence X280 multi-core, Linux capable RISC-V processor adding vector extensions and SiFive Intelligence Extensions, and optimized for AI/ML compute at the edge. SiFive Intelligence X280 key features: 64-bit RISC-V ISA with 8-stage dual-issue in-order pipeline, coherent multi-core, Linux capable based on U7 series core. SiFive Intelligence Extensions for ML workloads – BF16/FP16/FP32/FP64, int8 to 64 fixed-point data types 512-bit vector register length – Variable-length operations, up to 512-bits of data per cycle High-performance vector memory subsystem Memory parallelism provides cache miss tolerance Virtual memory support with precise exceptions Up to 48-bit addressing SiFive Intelligence includes software solutions to leverage the X280’s features and provide “great AI inference performance” using TensorFlow Lite. No […]

April 26, 2021May 6, 2022 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

M5Stack UnitV2 Linux AI camera features Sigmastar SSD202D SoC

We’ve written about SigmaStar SSD201/SSD202 processors several times now. The low-cost dual-core Cortex-A7 processor comes with 64MB or 128MB built-in RAM, and so far has been found in modules, smart displays, an SBC, and a gateway only available from China via stores like Taobao. But with mainline Linux support progressing nicely, it was only a matter of time until others make a product based on the processor, and M5Stack Unitv2 is an “AI” camera combining SSD202D processor with 128MB DDR3, and a GC2145 2MP camera sensor. M5Stack UnitV2 specifications: SoC – SigmaStar SSD202D dual-core Cortex-A7 processor @ 1.2 GHz with 128MB on-chip DDR3 Storage – 512MB on-chip NAND flash with around 100MB free space, MicroSD card socket Camera GC2145 1080p color sensor with USB UVC support 68° FoV, 60 cm to ∞ depth of field (DoF) Audio – Built-in microphone Connectivity – 2.4GHz WIFi 4 up to 150 Mbps USB […]

April 14, 2021April 14, 2021 by Jean-Luc Aufranc (CNXSoft) - 5 Comments

Perf-V Beetle board features GAP8 multi-core RISC-V AI MCU

GreenWaves Technologies introduced the GAP8 low-power RISC-V IoT processor optimized for artificial intelligence applications in 2018. The multi-core (8+1) RISC-V processor is especially suitable for image and audio algorithms including convolutional neural network (CNN) inference. The same year, the company launched the GAPUINO development kit that sold and (still sells) for $229 with QVGA camera and a multisensor board with four microphones, an STMicro VL53 Time of flight sensor, an IR sensor, a pressure sensor, a light sensor, a temperature & humidity sensor, and a 6-axis accelerometer/gyroscope. But there’s now a much more affordable solution to evaluate GAP8 multi-core RISC-V MCU with PerfXLab Perf-V Beetle board. Perf-V Beetle board specifications: MCU – GAP8 IoT Application Processor with 8x RISC-V compute cores, 1x RISC-V fabric controller core delivering up to 200 MOPS at 1mW and >8 GOPS at a few tens of mW System Memory – 64 Mbit SPI SRAM (LY68L6400SLIT) […]