Unit For Mac

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A few clicks, as described below, change PowerPoint units, for example, from inches to centimeters. Windows macOS Web PowerPoint displays the measurement system your computer uses, so to change from inches to metric (or vice versa), you make the change in Control Panel in. Make sure your Mac is connected to the external storage device (for example, using a USB cable or over a network). Click the Finder icon in the Dock to open a Finder window, then do one of the following to move your files. Move files to the storage device: Select one or more files on the desktop or in a folder, then drag them to the storage device, listed below Locations in the Finder sidebar. The MAC unit provides signal processing capabilities for the MCF5307 in a variety of applications including digital audio and servo control. Integrated as an execution unit in the processor’s OEP, the MAC unit implements a three-stage arithmetic pipeline optimized for 16 x 16 multiplies.

Mac Compatibility Mac Compatibility MacBook Air (Retina, 13-inch, 2020) MacBook Air (Retina, 13-inch, 2018 - 2019).

International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June-2013 52

ISSN 2229-5518

Design and Implementation of High- performance

MAC Unit

Shishir Kumar Das, Aniruddha Kanhe, R.H. Talwekar

Abstract—In real-life, embedded devices like mobile phone, notebook computers are made use of RISC processor and DSP .In Digital Signal Processing (DSP) applications the critical operations usually involve many multiplications and/or accumulations. So, for real time signal processing, the high speed multiplier accumulator (MAC) unit is always a key element to achieve a high-performance digital signal processing. The goal of this project is to design and implement the MAC unit for high-speed DSP applications. For designing the MAC unit various multipliers and adders are required. The MAC unit is implemented using VHDL, synthesized and simulated using Xilinx ISE 12.1.

Keywords—: Adders, CAD tools, multipliers, VHDL.

For

—————————— ——————————

N the majority of the Digital signal processing (DSP) ap- plications the critical operations usually involve many mul- tiplications and accumulations. So, for real time signal processing applications high throughput multiplier accumulator (MAC) is always a key element to achieve a high-performance digital signal processing. In the last few years, the main consid- eration of MAC design is to enhance its speed. This is because speed and throughput rate are always the concern of digital signal processing systems. Due to the increase of portable elec- tronic products, low power designs also become major consid- erations. This is because the limited battery energy of these portable products restricts the power consumption of the sys- tem.The main motive is to investigate various MAC architec- tures and the design techniques which are suitable for the im-
plementation of high throughput signal processing units.
The goal of this project is to design and implement Low power and high speed MAC unit. The total process is coded in VHDL. Finally, the whole process is implemented on Virtex 5
FPGA. The paper is organized as follows: Section 2 presents the overview of MAC unit. The implementation of MAC unit us- ing carry select Adder and Vedic Multiplier is discussed in Sec- tion 3. The implementation results are given in section 4, fol- lowed by conclusion in section 5.

A basic MAC unit consists of an adder, multiplier and an ac- cumulator. Usually, adders implemented are Carry-Select or Carry-Save adders, as speed is of utmost importance in DSP.

————————————————

• Shishir Kumar Das is currently working as Assistant Professor in KITE Raipur, INDIA. E-mail: shisdas@gmail.com

• Aniruddha Kanhe is currently working as Assistant Professor in KITE Raipur,INDIA E-mail: kanheaniruddha@gmail.com

R.H. Talwekar is currently working as Associate Prof. in DIMAT Raipur,

INDIA E-mail: ursk.talwekar@gmail.com
But if on chip area is to be considered then, Carry increment Adder can be used with an additional advantage of high speed [1]. One implementation of the multiplier could be Vedic Multi- plier [2].

2.1 Operation of MAC Unit

The inputs of MAC unit are fetched from memory cell and fed to the multiplier block of the MAC, which will perform multipli- cation and give the result to adder and then store the result in to a memory location. This entire process is to be achieved in a single clock cycle.
The proposed design consists of 32-bit floating point multiplier based on Vedic multiplication technique, 65-bit accumulator using carry select adder. To multiply the values of A and B, Floating point Vedic multiplier is used instead of conventional multiplier because Vedic multiplier can increase the speed of MAC unit. Carry select adder is used as an accumulator in this design. Apparently, together with the utilization of Vedic multi- plier approach, Carry select adder as the accumulator,
This MAC unit design is not only reducing the standby power consumption but also can enhance the MAC unit speed so as to gain better system performance.

The Fig.1 shows the block diagram of proposed MAC Unit consisting of 32 bit IEEE 754 based floating point Vedic Multi- plier unit.The result of multiplier is provided to the input of Ac- cumalotor through Carry select adder.

3.1 Multiplier Unit

In the proposed design of MAC Unit the Multiplier used is a 32
BIT IEEE 754 floating point multiplier based on Vedic multipli- cation technique. The multiplier for the floating point numbers represented in IEEE 754 format [3] can be divided in four sec- tions: Mantissa Calculation Unit, Exponent Calculation Unit, Sign Calculation Unit, and Control Unit [4].

IJSER © 2013 http://www.ijser.org

International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June-2013 53

ISSN 2229-5518


c4s4=c3+a2b2;
Now the final result of multiplication of A and B is c4s4s3s2s1s0.

3.2 Adder Unit

Calculator App For Mac

Fig. 1. Block Diagram of Proposed MAC Unit
The Vedic Multiplication technique is chosen for the implemen- tation of this unit. This technique gives promising result in terms of speed and power [2,4].The Vedic multiplication sys- tem is based on 16 Vedic sutras or aphorisms, which de- scribes natural ways of solving a whole range of mathematical problems. Out of these 16 Vedic Sutras the Urdhva- triyakbhyam sutra is suitable for this purpose. In this method the partial products are generated simultaneously which itself reduces delay and makes this method fast. The method for multiplication of two, 3 BITs number is shown Fig.2.
Fig.2 Vedic multiplication Method
A carry-select adder is divided into sectors, each of which – except for the least-significant performs two additions in paral- lel, one assuming a carry-in of zero, the other a carry-in of one. A four bit carry select adder generally consists of two rip- ple carry adders and a multiplexer. The carry-select adder is simple but rather fast. Adding two n-bit numbers with a carry select adder is done with two adders (two ripple carry adders) in order to perform the calculation twice, one time with the as- sumption of the carry being zero and the other assuming one. After the two results are calculated, the correct sum, as well as the correct carry, is then selected with the multiplexer once the correctcarry is known.A carry-select adder speeds 40% to
90%faster than RCA by performing additions in parallel and reducing the maximum carry path.

We are evaluating the performance of the high speed low power MAC Unit implemented using, 32 bit IEEE 754 Floating point multiplier based on Vedic Multiplication technique. The Table.1 shows the simulation result of Vedic multiplier and also comparision between conventional Array Multiplier aswellas Booth Multiplier. These multipliers are implemented using VHDL In order to get the power and delay report the multipliers are synthesized using Xilinx ISE tool and Spartan 2E FPGA is used. Table 1 compares the simulation result of multipliers with Vedic Multiplier on basis of time delay and power.

Table1. Comparison between multipliers

Consider the numbers A and B where A = a2a1a0 and B =
b2b1b0. The LSB of A is multiplied with the LSB of B:
s0=a0b0;
Then a0 is multiplied with b1, and b0 is multiplied with a1
And the result added together as:
c1s1=a1b0+a0b1;
Here c1 is carry and s1 is sum. Next step is to add c1 with the multiplication results of a0 with b2, a1 with b1 and a2 with b0. c2s2=c1+a2b0+a1b1 + a0b2;
Next step is to add c3 with the multiplication results of a1 with b2 and a2 with b1.
c3s3=c2+a1b2+a2b1; Similarly the last step
The Floating point multiplier Unit of proposed MAC is designed in VHDL and simulated using Modelsim Simulator. The design was synthesized using Xilinx ISE 12.1 tool targeting the Xilinx Virtex 5 Xc5vlx30-3-ff324 FPGA. The paper shows the efficient use of Vedic multiplication method to multiply two floating point numbers. The lesser number of LUTs verifies that the hard- ware requirement is reduced, thereby reducing the power con- sumption. The power is reduced affectively still not compro- mising delay so much. The Table 2 shows simulation result of floating point multiplier [5].

IJSER © 2013 http://www.ijser.org

International Journal of Scientific & Engineering Research, Volume 4, Issue 6, June-2013 54

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ISSN 2229-5518

Table2. Design Summary

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Unit For Mcv

Parameters

This work

[7]

Device

Virtex 5

FPGA

Virtex 2p

Time delay

5.246ns

3.070ns

Number of LUTs

966

1316

Number of IOs

99

100

Total dynamic power

27.29mW

55mW

The propose design shows the efficient use of Floating point Multiplier for implemtation of MAC Unit. As the hardware re- quirement of porposed Multiplier unit is less and also the dy- namic power dissption.Hence can be used for implementation of high performance MAC Unit.

REFERENCES

[1] R.UMA,Vidya Vijayan, M. Mohanapriya, Sharon PaulArea, Delay and Pow- er Comparison of Adder Topologies”, International Journal of VLSI design & Communication Systems(VLSICS) Vol.3, No.1, February 2012 DOI :

10.5121/vlsic.2012.3113 153

[2] Jagadguru Swami Sri Bharati Krisna Tirthaji Maharaja,“Vedic Mathematics

Sixteen Simple Mathematical Formulae from the Veda”, Delhi 1965. [3] IEEE 754-2008, IEEE Standard for Floating-Point Arithmetic, 2008.

[4] Aniruddha Kanhe, Shishir Kumar Das and Ankit Kumar Singh, “Design And Implementation Of Low Power Multiplier Using Vedic Multiplication Tech- nique,” International Journal of Computer Science and Communication (IJCSC) Vol. 3, No. 1, January-June 2012, pp. 131-132.

[5] Aniruddha Kanhe, Shishir Kumar Das, Ankit Kumar Singh, “Design and Implementation of Floating Point Multiplier based on Vedic Multiplication Technique”, International Conference on Communication, Information and Computing Technology (ICCICT-2012) Co- Sponsored by IEEE System.

[6] Prabha S., Kasliwal, B.P. Patil, and D.K Gautam,“Performance Evaluation of Squaring Operation by Vedic Mathematics”, IETE Journal of Research, 57(1), Jan-Feb 2011.

[7] Kavita Khare, R.P.Singh, Nilay Khare,”Comparison of pipelined IEEE-754 standard floating point multiplier with unpipelined multiplier” Journal of Sci-

entific & Industrial Research Vol.65, pages 900-904 November 2006.

IJSER © 2013 http://www.ijser.org

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Unit for mac keyboardMachining

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Unit For Sale Mackay

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Unit For Mac Air

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Shell and Tools

  • We updated NuGet to 5.7 RTM.
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  • We fixed an issue where Visual Studio was crashing on macOS Big Sur. If you have already upgraded macOS to Big Sur and are not able to run VS for Mac, please download the latest installer from https://visualstudio.microsoft.com/vs/mac/ to install the latest stable version and then install this preview from the Preview channel.
  • We made fixes to address a handful of stability and performance issues.
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Tools for Unity

  • We fixed a bug where breakpoints would not be hit if they were set while already debugging.
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Version Control

  • We fixed an issue with version control tabs not showing up.
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Web and Azure

  • We updated the .NET Core SDK (3.1.302 SDK and 2.1.20 runtime).
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  • We fixed an issue where building Angular projects failed to find clang++.
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  • We fixed an issue with unresponsive Add gRPC Service Reference dialogs.
  • We added support for adding new Open AI & gRPC service references to .NET Core projects.
  • We fixed an issue causing Cannot load solution on VisualStudio for Mac.
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Xamarin

  • Support for Xcode 11.5 and 11.6.
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  • We fixed a handful of crashes reported by users.
  • We fixed a few instances where VoiceOver would read labels of elements on Wizard template pages twice.
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  • We fixed an issue where color contrast was too low for the expand/collapse button in the Apple Developer account dialog.

Known Issues

Mac

The following is a list of all existing known issues in Visual Studio 2019 for Mac version 8.7:

  • In rare cases, it's possible to be up to date with everything but the .NET Core 3.1.300 SDK. If you enter into this configuration and update to .NET Core 3.1.300 using the updater, the notification to update the .NET Core SDK will not disappear until the IDE is restarted.
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