The document describes several projects completed at ISRO Satellite Centre related to satellite systems. It provides details of 8 projects including the project name, location, client, operating system, tools used, programming languages, descriptions, and responsibilities. The projects involved migrating software, developing telemetry interface and simulation software, onboard software for attitude and orbit control, optimizing magnetic torquer design, star pattern simulation, and resource accounting software.
Software AI Accelerators: The Next Frontier | Software for AI Optimization Su...Intel® Software
Software AI Accelerators deliver orders of magnitude performance gain for AI across deep learning, classical machine learning, and graph analytics and are key to enabling AI Everywhere. Get started on your AI Developer Journey @ software.intel.com/ai.
We were pioneers: early applications of dwn simulations_2Piero Belforte
The early applications (1970s) of a revolutionary electrical circuit simulation method (DWN) are presented including device modelling and signal integrity driven design of high speed digital modules. These modules were utilized to develop the prototypes of digital switching systems deployed in Italian Telecom network in the 1970s.
Use Variable Rate Shading (VRS) to Improve the User Experience in Real-Time G...Intel® Software
Variable-rate shading (VRS) is a new feature of Microsoft DirectX* 12 and is supported on the 11th generation of Intel® graphics hardware. Get an overview and learn best practices, recommendations, and how to modify traditional 3D effects to take advantage of VRS.
Advanced Single Instruction Multiple Data (SIMD) Programming with Intel® Impl...Intel® Software
Explore practical elements, such as performance profiling, debugging, and porting advice. Get an overview of advanced programming topics, like common design patterns, SIMD lane interoperability, data conversions, and more.
The growing interest in FPGA-based solutions for accelerating compute demanding algorithms is pushing the need for new tools and methods to improve productivity. High-Level Synthesis (HLS) tools already provide an handy way to describe an FPGA-based hardware implementations starting from a software description of an algorithm. However, HLS directives allow to improve the hardware design only from a computational perspective, requiring a manual code restructuring in case memory transfer needs optimizing. This aspect limits the effectiveness of Design Space Exploration (DSE) approaches that only target HLS directives. Therefore, we present a comprehensive methodology to support the designer in the generation of optimal HLS-based hardware implementations. First, we propose an automated roofline model generation that directly operates on a C/C++ description of the target algorithm. The approach enables a fast evaluation of the operational intensity of the target function and visualizes the main bottlenecks of the current HLS implementation, providing guidance on how to improve it. Second, we introduce a DSE methodology for quickly evaluating different HLS directives to identify an optimal implementation. We report the DSE performance when running on the PolyBench test suite, outperforming previous automated solutions in the literature. Finally, we illustrate the process of accelerating by means of our framework a complex application such as the N-body physics simulation algorithm, achieving results comparable to bespoke state-of-the-art implementations.
In this deck from the Perth HPC Conference, Rob Farber from TechEnablement presents: AI is Impacting HPC Everywhere.
"The convergence of AI and HPC has created a fertile venue that is ripe for imaginative researchers — versed in AI technology — to make a big impact in a variety of scientific fields. From new hardware to new computational approaches, the true impact of deep- and machine learning on HPC is, in a word, “everywhere”. Just as technology changes in the personal computer market brought about a revolution in the design and implementation of the systems and algorithms used in high performance computing (HPC), so are recent technology changes in machine learning bringing about an AI revolution in the HPC community. Expect new HPC analytic techniques including the use of GANs (Generative Adversarial Networks) in physics-based modeling and simulation, as well as reduced precision math libraries such as NLAFET and HiCMA to revolutionize many fields of research. Other benefits of the convergence of AI and HPC include the physical instantiation of data flow architectures in FPGAs and ASICs, plus the development of powerful data analytic services."
Learn more: http://www.techenablement.com/
and
http://hpcadvisorycouncil.com/events/2019/australia-conference/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Software AI Accelerators: The Next Frontier | Software for AI Optimization Su...Intel® Software
Software AI Accelerators deliver orders of magnitude performance gain for AI across deep learning, classical machine learning, and graph analytics and are key to enabling AI Everywhere. Get started on your AI Developer Journey @ software.intel.com/ai.
We were pioneers: early applications of dwn simulations_2Piero Belforte
The early applications (1970s) of a revolutionary electrical circuit simulation method (DWN) are presented including device modelling and signal integrity driven design of high speed digital modules. These modules were utilized to develop the prototypes of digital switching systems deployed in Italian Telecom network in the 1970s.
Use Variable Rate Shading (VRS) to Improve the User Experience in Real-Time G...Intel® Software
Variable-rate shading (VRS) is a new feature of Microsoft DirectX* 12 and is supported on the 11th generation of Intel® graphics hardware. Get an overview and learn best practices, recommendations, and how to modify traditional 3D effects to take advantage of VRS.
Advanced Single Instruction Multiple Data (SIMD) Programming with Intel® Impl...Intel® Software
Explore practical elements, such as performance profiling, debugging, and porting advice. Get an overview of advanced programming topics, like common design patterns, SIMD lane interoperability, data conversions, and more.
The growing interest in FPGA-based solutions for accelerating compute demanding algorithms is pushing the need for new tools and methods to improve productivity. High-Level Synthesis (HLS) tools already provide an handy way to describe an FPGA-based hardware implementations starting from a software description of an algorithm. However, HLS directives allow to improve the hardware design only from a computational perspective, requiring a manual code restructuring in case memory transfer needs optimizing. This aspect limits the effectiveness of Design Space Exploration (DSE) approaches that only target HLS directives. Therefore, we present a comprehensive methodology to support the designer in the generation of optimal HLS-based hardware implementations. First, we propose an automated roofline model generation that directly operates on a C/C++ description of the target algorithm. The approach enables a fast evaluation of the operational intensity of the target function and visualizes the main bottlenecks of the current HLS implementation, providing guidance on how to improve it. Second, we introduce a DSE methodology for quickly evaluating different HLS directives to identify an optimal implementation. We report the DSE performance when running on the PolyBench test suite, outperforming previous automated solutions in the literature. Finally, we illustrate the process of accelerating by means of our framework a complex application such as the N-body physics simulation algorithm, achieving results comparable to bespoke state-of-the-art implementations.
In this deck from the Perth HPC Conference, Rob Farber from TechEnablement presents: AI is Impacting HPC Everywhere.
"The convergence of AI and HPC has created a fertile venue that is ripe for imaginative researchers — versed in AI technology — to make a big impact in a variety of scientific fields. From new hardware to new computational approaches, the true impact of deep- and machine learning on HPC is, in a word, “everywhere”. Just as technology changes in the personal computer market brought about a revolution in the design and implementation of the systems and algorithms used in high performance computing (HPC), so are recent technology changes in machine learning bringing about an AI revolution in the HPC community. Expect new HPC analytic techniques including the use of GANs (Generative Adversarial Networks) in physics-based modeling and simulation, as well as reduced precision math libraries such as NLAFET and HiCMA to revolutionize many fields of research. Other benefits of the convergence of AI and HPC include the physical instantiation of data flow architectures in FPGAs and ASICs, plus the development of powerful data analytic services."
Learn more: http://www.techenablement.com/
and
http://hpcadvisorycouncil.com/events/2019/australia-conference/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
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With the rise of IoT and the increasing complexity of applications, clouds, networks and infrastructure, the battle to keep your data and your infrastructure safe from attackers is getting harder. As groups of bad actors collaborate, sharing information and offering illegal access, and botnets as a service, terabits of attack can be launched cheaply. Meanwhile, it’s hard to find enough security analysts to catch and prevent these attacks.
This is where community collaboration and open source efforts like Apache Metron come in. Metron presents a comprehensive framework for application and network, security built on Apache Hadoop and open source Streaming Analytics(ie Apache Nifi, Apache Kafka) tool’s highly scalable data management and processing stacks. Advanced features like profiling, machine learning, and visualization work with real-time streaming detection to make your SOC analysts more efficient, while the intrinsic extensibility of open source helps your data scientists get security insights out of the lab and into production fast.
We will discuss and demonstrate how some real-world businesses and managed service providers are using Apache Metron to identify and solve security threats at scale, and some approaches and ideas for how the platform can fit into your security architecture.
Speaker: Laurence Da Luz, Senior Solutions Architect, Hortonworks
1. Details of Previous Projects (at ISRO SATELLITE CENTER)
Project Name Migration of HILS software from DEC Alpha to Intel
Work Location ISRO Satellite Centre, Bangalore
Client Internal to ISRO
Operating System Digital Unix, Linux
Tools RUP
Language X-Motif, C, C++, Socket programming, IPC
Project Description HILS software was coded with FORTRAN and C language on Digital Unix
platform. As per the requirements, migrating and making the AOCE testing
software from DEC Alpha workstations compatible to Linux 32-bit Intel
system, and for the uniformity of the HILS software.
Responsibilities • Code walk through of the existing HILS software.
• Designed the software with the help of Rational Rose Development Suite
and created Use-case diagrams, Activity diagrams, Class diagrams.
• Comparing Digital Unix system level standards with Linux standards.
• Coding of modules like dynamics equations solving, thruster module, FEP
data processing, Magnetic torque processing, wheel processing, LAM
mode etc., in C language 5. Open-loop & Closed loop testing
Project Name Telemetry Interface Software
Work Location ISRO Satellite Centre, Bangalore
Client Internal to ISRO
Operating System Digital Unix
Tools
Language X-Motif, C, Socket programming, shell scripting, IPC
Project Description Telemetry processing is to measure the Space Craft's characteristics. The
software acquires Telemetry data from Front End processor, finds the frame-
sync, processes the data according to the parameters' database, and archives
the data for post-processing.
Responsibilities Involved in the requirements gathering, analysis, preparation of test-cases &
results, leading the team for completion of the requirement, delivery &
maintenance. Project: IRS-P5, Cartosat -2 & SRE
• Telemetry data acquisition from FEP (Front End Processor) for both 1kbps
& 4kbps data speed.
• Identification of Frame Sync for normal, dwell and playback data.
• Creation of master database for Telemetry parameters.
• Real-time TM Data Processing.
• Real-time Page display and plotting for normal, dwell and playback
Telemetry data.
• Real-time Plotting provision for normal, dwell and playback TM data.
• Archiving of the raw data.
• Post processing for the archived data for normal and 4#formats of playback
data.
Project Name AOCE Simulation Software (Attitude & Orbit Control Electronics)
Work Location ISRO Satellite Centre, Bangalore
Client Internal to ISRO
Operating System Digital Unix
Tools Rational Rose
2. Language X-Motif, C, Socket programming, shell scripting, IPC
Project Description This software is developed to validate AOCE system (Attitude and Orbit
Control Electronics), which receives torque signals from actuators, then solves
spacecraft dynamic equations, and gives the calculated error rates to drive the
servo table.
Responsibilities Responsible for code changes & testing of Data Acquisition from AOCE,
Actuator Processings, Dynamics equations solving, Sensor Simulations, GUI
developed for initial conditions, to control the simulation, for storage &
communication.
Project Name AOCE On-Board Software
Work Location ISRO Satellite Centre, Bangalore
Client Internal to ISRO
Operating System Sun Solaris, Digital Unix
Tools Rational Rose
Language C++
Project Description This software continuously monitors the change in the position of spacecraft.
AOCE computes the errors with respect to sensors mounted on spacecraft and
sends back the error rates to the actuators.
Responsibilities Worked as the Team member for analyzing the requirements, designing,
coding and conducting unit level
Project Name Magnetic Torquer's Optimized Design
Work Location ISRO Satellite Centre, Bangalore
Client Internal to ISRO
Operating System Linux
Tools
Language C
Project Description Magnetic Torquer is an actuator to control the satellite, which works on the
principle of earth's magnetic attraction. This produces the magnetic force
depending upon factors like, dimensions of core and coil, number of rotations
of coil and the number of layers around the core. These factors have to be
optimized to produce the required magnetic force. Here Genetic algorithms
Technique, one of the optimizing search techniques based on principles of
natural selection is used in order to optimize the design of the magnetic
Torquer.
Responsibilities Requirement capturing, designing, coding and testing of the software
Project Name Dynamic Multi Star Simulator (DMSS)
Work Location ISRO Satellite Centre, Bangalore
Client Internal to ISRO
Operating System Digital Unix
Tools
Language C, Socket programming, IPC
Project Description DMSS simulates the star pattern along with star coordinates, intensity of the
pattern, and back-light of the screen at a given instant of time. The position of
the spacecraft on-board can be identified with the help of star pattern
produced by the DMSS.
Responsibilities Worked in requirement capturing, designing, coding and testing. Modules
involved are Star catalog, Star identification algorithm and Intensity
3. verification software.
Project Name System Resource Accounting Software
Work Location ISRO Satellite Centre, Bangalore
Client Internal to ISRO
Operating System Digital Unix
Tools
Language shell scripting, Unix System Administration
Project Description This Software developed for Digital Unix NIS Server, which helps the System
Administrator to monitor the system resources statistics of all the hosts
connected in the local network, tracked on a daily, monthly, and as well as
yearly basis with respect to prime and non-prime time usage.
Responsibilities Responsible for collecting the requirements from users and analyzing with the
different Unix flavors features, coding, testing with different reports.