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NVIDIA and Open Robotics, the company behind the popular robot operating system ( ROS), have long supported each other. But the companies are taking the partnership to another level with ROS 2, the more hardened, secure version of the middleware suite.
Accelerated performanceNVIDIA and Open Robotics are working together to accelerate the performance of ROS 2 on NVIDIA’s Jetson edge AI platform and GPU-based systems. The initiatives will reduce development time and improve performance for developers seeking to incorporate computer vision and machine learning functionality into their ROS-based applications.
“The ROS framework is CPU-centric today,” said Murali Gopalakrishna, head of product management for autonomous machines and GM for robotics at NVIDIA. “We’re making it more heterogeneous to leverage GPUs and deep neural networks and other hardware accelerators. This is very important to improve the quality of robots and the speed to market for robotics companies.”
Open Robotics will enhance ROS 2 to enable efficient management of data flow and shared memory across GPU and other processors present on the NVIDIA Jetson edge AI platform. The companies said this will improve the performance of applications that have to process high-bandwidth data from sensors such as cameras and LiDARs in real time.
“As more ROS developers leverage hardware platforms that contain additional compute capabilities designed to offload the host CPU, ROS is evolving to make it easier to efficiently take advantage of these advanced hardware resources,” said Brian Gerkey, CEO, Open Robotics. “Working with an accelerated computing leader like NVIDIA and its vast experience in AI and robotics innovation will bring significant benefits to the entire ROS community.”
Functional block diagram of Isaac Sim showing robot model, environment model, and 3D asset inputs. | Credit: NVIDIA
The companies are also developing simulation interoperability between Open Robotics’s Ignition Gazebo and NVIDIA Isaac Sim on Omniverse. Isaac Sim already supports ROS 1 and ROS 2 out of the box. But connecting the two allows ROS developers to more easily move their robots and environments between each simulator and capitalize on their respective benefits.
NVIDIA highlights the ability of Isaac Sim to generate synthetic data to train and test perception models. Once Isaac Sim generates synthetic datasets, they can be fed into NVIDIA’s AI model adaptation platform to adapt perception models for a robot’s specific working environment.
The latest version of Isaac Sim includes significant support for ROS developers. Some of the more compelling examples of this, NVIDIA said, are the ROS 2 Navigation stack and the MoveIt Motion Planning Framework. Other examples of Isaac Sim’s support of ROS include:
ROS April Tag
ROS Stereo Camera
ROS TurtleBot3 Sample
ROS Manipulation and Camera Sample
Native Python ROS Usage
“Developers could take domain-specific data for a hospital, a warehouse, or a store,” Gopalakrishna said. “They can use that data, our tools and augment that with real-world data to build robust, scalable models in photo-realistic environments that obey the laws of physics.” He added that NVIDIA will release pre-trained models.
NVIDIA also released new Isaac GEMs for ROS. Isaac GEMs for ROS are hardware accelerated packages that make it easier for ROS developers to build high-performance solutions on the Jetson platform, when compared to CPU-only packages. The focus of these GEMs is on improving throughput on image processing and on deep neural network-based perception models that are of growing importance to roboticists.
“ROS started as a hobby project, but people started to build on it, and it took on a life of it’s own,” said Gopalakrishna. “There has been a lot of effort to harden ROS 2 and its performance. ROS 2 takes learnings from ROS 1, made it more streamlined and fixed shortcomings such as message passing and DDS. This makes ROS 2 more scalable and performant. Now it makes even more sense for us to offer hardware acceleration.”
So we heard TSMC has some order cancellations, and some capacity coming online. I am guessing AMD is getting a good chunk of the N7 and N6 capacity left behind others, and also new N5 capacity for Zen 4 and RDNA 3.
In the N7 (and N6?) will continue to have good sales and good margins for AMD, maybe this 15% - 20% capacity growth per quarter can continue for another year unabated...
3rd tier of RDNA3 will still be faster than current highest end 6900 XT and 3090 (while using a cheap 128 bit bus width), and will be on N6 process technology, unlike top 2 tiers of RDNA 3, which will be on N5, and will be chiplet based.
Seems almost unbelievable. Well, we don't know the die size...
So I am still a little confused about this first new assembly facility for 3D packaging. I believed this is the one they called AP6. It is supposed have its equipment moved in in this, H2 2021 and another one 2.5D / 3D packaging facility in H2 2022. Some update from Digitimes: -------------------------------------------
TSMC soon to start equipment move-in at new advanced packaging fab in Taiwan, says report Jessie Shen, DIGITIMES, TaipeiTuesday 28 September 20210
TSMC is expected to kick off equipment move-in at its new advanced packaging fab in Chunan, northern Taiwan later in the second half of this year, according to a report by Taiwan's Central News Agency (CNA). The fab will be dedicated to providing the foundry's in-house developed SoIC (system on integrated chips) technology.
TSMC is also scheduled to complete constructing another advanced packaging fab designed for the manufacture of chips using its advanced 2.5D packaging technology in 2022, the report said.
TSMC has disclosed the foundry expects to commercialize its SoIC technology at the newly-established fab in Chunan in the second half of 2022. TSMC has been promoting its 3DFabric family of 3D silicon stacking and advanced packaging technologies, with plans to have five fabs dedicated to providing its 3DFabric advanced packaging solutions by the end of next year, company CEO CC Wei was quoted as saying in previous reports.
TSMC in 2020 introduced 3DFabric as its comprehensive family of 3D silicon stacking and advanced packaging technologies. 3DFabric, which complements the foundry's advanced semiconductor technologies, consists of the foundry's backend CoWoS and InFO 3D stacking technologies, and the newly-developed SoIC for 3D heterogeneous integration.