Floorplanning involves determining the approximate locations and shapes of modules on an integrated circuit to optimize the design for factors like area, wirelength, and timing. The goals are to partition the design into functional blocks, arrange the blocks, place macros and I/Os, and design the power distribution grid. Floorplanning algorithms use techniques like integer programming, rectangular dual graphs, and hierarchical and simulated annealing approaches to explore the design space and generate optimized floorplans. The outputs include the die area, placement of I/Os and macros, a preliminary power grid design, and definitions of standard cell placement regions.
Routing in Integrated circuits is an important task which requires extreme care while placing the modules and circuits and connecting them with each other.
VLSI Physical Design Flow(http://www.vlsisystemdesign.com)VLSI SYSTEM Design
Learning becomes Fun..
When tedious & difficult topics like Chip Design are explained in simple n creative videos....https://www.udemy.com/vlsi-academy
This is a custom GUI, which eases fixing violations either by adding buffer, cloning or sizing. Drop down menu item is created in ICC2 layout window. Desired terminals can be selected by dragging or adding points in rectilinear fashion and desired locations can be selected for adding new buffer.
Physical verification will verify that the post-layout netlist and the layout are equivalent. i.e. all connections specified in the netlist is present in the layout. This article explains physical verification.
TYPES OF PLACEMENT,GOOD PLACEMENT VS. BAD PLACEMENT ,ALGORITHMS, ASIC DESIGN FLOW DIAGRAM,DEFINITION OF PLACEMENT,TECHNIQUES USED FOR PLACEMENT,PLACEMENT TRENDS,SOLUTIONS
Routing in Integrated circuits is an important task which requires extreme care while placing the modules and circuits and connecting them with each other.
VLSI Physical Design Flow(http://www.vlsisystemdesign.com)VLSI SYSTEM Design
Learning becomes Fun..
When tedious & difficult topics like Chip Design are explained in simple n creative videos....https://www.udemy.com/vlsi-academy
This is a custom GUI, which eases fixing violations either by adding buffer, cloning or sizing. Drop down menu item is created in ICC2 layout window. Desired terminals can be selected by dragging or adding points in rectilinear fashion and desired locations can be selected for adding new buffer.
Physical verification will verify that the post-layout netlist and the layout are equivalent. i.e. all connections specified in the netlist is present in the layout. This article explains physical verification.
TYPES OF PLACEMENT,GOOD PLACEMENT VS. BAD PLACEMENT ,ALGORITHMS, ASIC DESIGN FLOW DIAGRAM,DEFINITION OF PLACEMENT,TECHNIQUES USED FOR PLACEMENT,PLACEMENT TRENDS,SOLUTIONS
TensorFlow Korea 논문읽기모임 PR12 243째 논문 review입니다
이번 논문은 RegNet으로 알려진 Facebook AI Research의 Designing Network Design Spaces 입니다.
CNN을 디자인할 때, bottleneck layer는 정말 좋을까요? layer 수는 많을 수록 높은 성능을 낼까요? activation map의 width, height를 절반으로 줄일 때(stride 2 혹은 pooling), channel을 2배로 늘려주는데 이게 최선일까요? 혹시 bottleneck layer가 없는 게 더 좋지는 않은지, 최고 성능을 내는 layer 수에 magic number가 있는 건 아닐지, activation이 절반으로 줄어들 때 channel을 2배가 아니라 3배로 늘리는 게 더 좋은건 아닌지?
이 논문에서는 하나의 neural network을 잘 design하는 것이 아니라 Auto ML과 같은 기술로 좋은 neural network을 찾을 수 있는 즉 좋은 neural network들이 살고 있는 좋은 design space를 design하는 방법에 대해서 얘기하고 있습니다. constraint이 거의 없는 design space에서 human-in-the-loop을 통해 좋은 design space로 그 공간을 좁혀나가는 방법을 제안하였는데요, EfficientNet보다 더 좋은 성능을 보여주는 RegNet은 어떤 design space에서 탄생하였는지 그리고 그 과정에서 우리가 당연하게 여기고 있었던 design choice들이 잘못된 부분은 없었는지 아래 동영상에서 확인하실 수 있습니다~
영상링크: https://youtu.be/bnbKQRae_u4
논문링크: https://arxiv.org/abs/2003.13678
A natural extension of the Random Access Machine (RAM) serial architecture is the Parallel Random Access Machine, or PRAM.
PRAMs consist of p processors and a global memory of unbounded size that is uniformly accessible to all processors.
Processors share a common clock but may execute different instructions in each cycle.
A separately excited dc motor is driven from a 240v, 50HZ supply via a HC
SCR-bridge with a fly-wheel diode. The motor has an armature resistance
1Ω, an armature voltage constant Kv of 0.8 V. s/rad. The field current is
constant. Assume steady armature current. Determine the armature current
and torque for 1600 rpm and a firing angle delay of a) 30° b) 60
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
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Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
2. Outlines
Physical Design –Overall Flow
Introduction
Floor Plan Terminology
Goals Of Floor plan
Floor Plan Inputs
Floor Plan Problem
Challenges In Floor Plan
Floor Planning vs Placement
Design Style Specific Issues
Estimatining Cost Of Floorplan
How To Determine Area
How TO Determine Wire Length
Dead Space
Silicing Strucure
Floor Planning Algorithms
Floor Plan Outputs
4. Floor planning
Floorplanning nothing but a plan a
house floorplanning.
Find approixmate locations of a set
of modules that need to placed on
layout surface.
Avilable region typically considered
rectangular, modules are also
typically rectangular In shape but
there can be exceptions(e.g-L-
shape).
6. Goals of Floor Plan
Partition the design into functional blocks
Arrange the blocks on a chip
Place the Macros
Decide the location of the I/O pads
Decide the location and number of the power
pads
Decide the type of power distribution
8.
Synthesis Netlist: A netlist is a description of the connectivity
ofan electronic circuit. In its simplest form, a netlist consists of a
list of the electronic components in a circuit and a list of the
nodes they are connected to. It can be in the form of Verilog or
VHDL. This netlist is produced during logical, synthesis, which
takes place prior to the physicaldesign stage.
• Physical Library: Physical/Reference libraries contains
physical information of standard, macro and pad cells,which is
necessary for placement and routing. These libraries define
placement file like height of placement ows,minimum width
resolution, preferred routing directionpitch of routing tracks
etc.
Contd.
9. • Power Requirement: Power & Ground nets.
• Floor planning control parameters: Die size estimation, core size,
aspect ratio, core height, core width.
• Timing Constraints: SDC constraints. Clock constraints -
max skew, max and min insertion delay, no. of clock
domains, clock start points (whether portlevel or internally
generated)
• Logical libraries: This library file which provides timing and
functionality information an each and every standard cellsused in
the design. It also provides timing information of hard macros
such as IP,ROM, RAM etc.
Contd.
10. Floorplanning Problem
The floorplanning problem is to plan the positions and
shapes of the modules at the beginning of the design cycle
to optimize the performance of the circuits:
chip area
total wirelength
delay of critical paths
routability
others, e.g., noise, heat dissipation, etc.
• In floorplanning several alternatives for each block are
considered
11. Challenges in Floor Plan
Die Area
Congestion
Timing
Power Network Design
Electro-Migration
IR Drop
12. Floorplanning vs Placement
Both determine block positions to optimize the circuit
Performance.
Floorplanning:
Details like shapes of blocks, pin assignments, etc. are
not yet fixed (blocks with flexible shape are also called
soft Blocks).
Placement:
Details like module shapes and I/O pin positions are fixed
(blocks with no flexibility in shape are also called hard
blocks).
13. Points to note:
Floor planning problem is more difficult to handle as
compared to placement
Multiple choice for the shape of a block.
In some of the VLSI design styles, the two problems are
identical.
15. Design Style Specific Issues
– All the steps required for general cells.
• Full Custom
• Standard Cell
– Dimensions of all cells are fixed.
– Floorplanning problem is simply the placement problem.
– For large netlists, two steps:
• First do global partitioning.
• Placement for individual regions next.
• Gate Array
– Floorplanning problem same as placement
problem.
16.
The number of feasible solutions of a floorplanning
problem is very large.
– Finding the best solution is NP-hard.
Several criteria used to measure the quality of
floorplans:
Estimating Cost of a Floorplan
a) Minimize area
b) Minimize total length of wire
c) Maximize routability
d) Minimize delays
e) Any combination of above
17. –Not difficult.
–Can be easily estimated because the dimensions of each
block is known.
–Area Acomputed for each candidate floorplan.
• How to determine area?
18. • How to determine wire length?
– A coarse measure is used.–Based on a model where all I/O pins
of the blocks are merged and assumed to reside at its center.
– Overall wiring length L = Σi,j(cij* dij)
where
cij: connectivity between blocks i and j
dij: Manhattan distances between the centres of
rectangles of blocks i and j
• Typical cost function used:
where w1 and w2 are user-specified
parameters.
19. Dead space:
Some times we estimate the goodness of floorplan
that is by measuring Dead Space.
Deadspace is the space that is wasted:
Minimizing area is the same as minimizing deadspace.
Deadspace percentage is computed as
((A - Σ Ai ) / Σ Ai) × 100%
A=H . W Ai=wi×hi
20. Slicing Structure
Definition
– A rectangular dissection that can be obtained by repeatedly
splitting rectangles by horizontal and vertical lines into
smallerrectangles.
Slicing
Tree–A binary tree that models a slicing
structure.– Each node represents a vertical cut line(V), or a horizontal cut
line(H).
• A third kind of node called Wheel (W)appears for non-sliceable
floorplans (discussed later).
–Each leaf is a basic block
(rectangle).
23. Floorplanning Algorithms
• Several broad classes of algorithms:
– Integer programming based
– Rectangular dual graph based
– Hierarchical tree based
– Simulated annealing based–Other variations
24. Integer Linear Programming Formulation
• The problem is modeled as a set of linear equations using 0/1
integer variables.
ILP solver used to obtain optimal solution based on a defined
cost function.
Can be use only for small problem instances
-Very high computional complexity.
25. Rectangular Dual-Graph Approach
• Basic Concept:
–Output of partitioning algorithms represented by a graph.
–Floorplans can be obtained by converting the graph into
its rectangular dual.
• The rectangular dual of a graph satisfies the following
properties:
– Each vertex corresponds to a distinct rectangle.
– For every edge, the corresponding rectangles are adjacent.
26. A Rectangular Floorplan & its Dual Graph
• Without loss of generality, we
assume that a rectangular
floorplan contains no cross
junctions.
1
2
5
43
• Under this assumption, the dual
graph of a rectangular floorplan is a
planar triangulated graph (PTG).
27. • Every dual graph of a rectangular floorplan (without cross
junction) is a PTG.
• However, not every PTG corresponds to a rectangular
floorplan.
28. Drawbacks
• A new approach to floorplanning, in which many sub-problems
are still unsolved.
• The main problem concerns the existence of the rectangular
dual, i.e. the elimination of complex triangles.
– Select a minimum set E of edges such that each complex
triangle has at least one edge in E.
– A vertex can be added to each edge of E to eliminate all
complex triangles.
– The weighted complex triangle elimination problem has been
shown to be NP-complete.
•Some heuristics are available.
29. Hierarchical Approach
• Widely used approach to floorplanning.
– Based on a divide-and-conquer paradigm.
– At each level of the hierarchy, only a small
number of rectangles are considered.
• A small graph, and all possible floorplans.
30. – After an optimal configuration for the three modules has been
determined, they are merged into a larger module.
–The vertices ‘a’, ‘b’, ‘c’ are merged into a super vertex at the
next level.
• The number of floorplans increases exponentially with the
number of modules ‘d’ considered at each level.
–‘d’ is thus limited to a small number (typically d < 6).
Contd.
32. Hierarchical Approach :: Bottom-Up
• Hierarchical approach works best in bottom-up fashion.
• Modules are represented as vertices of a graph, while edges
represent connectivity.
– Modules with high connectivity are clustered together.
– An optimal floorplan for each cluster is determined by
exhaustive enumeration.
–The cluster is merged into a larger module for high-level
processing.
• Number of modules in each cluster
≤d.
33. • A Greedy Procedure
– Sort the edges in decreasing weights.
– The heaviest edge is chosen, and the two modules of
the edge are clustered in a greedy fashion.
• Restriction: number of modules in each cluster ≤d.
– In the next higher level, vertices in a cluster are merged,
and edge weights are summed up accordingly.
Contd.
34. • Problem
– Some lightweight edges may be chosen at higher levels in
the hierarchy, resulting in adjacency of two clusters of highly
incompatible areas.
• Possible solution
– Arbitrarily assign a small cluster to a neighboring cluster
when their sizes will be too small for processing at a higher
level of the hierarchy.
Contd.
36. Hierarchical Approach :: Top-Down
• The fundamental step is the partitioning of modules.
– Each partition is assigned to a child floorplan.
– Partitioning is recursively applied to the child floorplans.
• Major issue here is to obtain balanced graph partitioning.
– k-way partitioning, in general.
• Not very widely used due to the difficulty of obtaining
balanced partitions.
37. • One can combine top-down and bottom-up approaches.
– Apply bottom-up technique to obtain a set of clusters.
– Apply top-down approach to these clusters.
Contd.
38. Simulated Annealing
• Important issues in the design of a simulated annealing
optimization problem:
1. The solution space.
2. The movement from one solution to another.
3. The cost evaluation function.
• A solution by Wong & Liu is applicable to sliceable floorplans
only.
– Floorplan can be represented by a tree.
– Postfix notations used for easy representation and
manipulation.
39. Some Notations
• Dissection operators defined:
– ijH means rectangle j is on top of rectangle i.
– ijV means rectangle j is on left of rectangle i.
• Normalized Polish expression:
– A Polish expression corresponding to a floorplan is called
normalized if it has no consecutive H’s or V’s.
– Used for the purpose of removing redundant solutions from
the solution space.
40. • There may be several several Polish expressions
that correspond to the same slicing floorplan.
• We have seen earlier that the same floorplan can
have more than one slicing tree.
Contd.
42. Parameters of the Algorithm
• Solution Perturbations (Move)
a) Swap two adjacent operands
b) Complement a series of operators between two operands
(called a chain).
V′= H and H′= V
c) Swap two adjacent operand and operator.
• We accept a move only it is results in a normalized
expression.
43. • Cost Function:–
Typical cost function used:
Cost = w1* A + w2*L
where A is the area of the smallest rectangle enveloping the
given basic rectangles,
L is the overall interconnection length, w1and w2are user-
specified parameters.
– Only move “c” may result in a non-normalized
solution.
– We need to check only when move “c” is applied.
Contd.