Where Else Would I Go Now

I feel peaceful when I have the right knowledge. In the process of growing as an Electronics engineer, I collected many books, compiled projects, downloaded pages etc, which all went away at the moment I needed them most--when my laptop was stolen. So, now I am collecting my personal notes here in this blog.

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The higher the number of servers belonging to a network, the more versatility you can expect to find on it—but this is where the dark side of human nature creeps in and spoils the dream.

Alex Charalabidis, The Book of IRC

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Twisted Transistor!

Computers are integer machines and are capable of representing real numbers only by using complex codes. The most popular code for representing real numbers is called the IEEE Floating-Point Standard. The term floating point is derived from the fact that there is no fixed number of digits before and after the decimal point; that is, the decimal point can float. There are also representations in which the number of digits before and after the decimal point is set, called fixed-point representations. In general, floating-point representations are slower and less accurate than fixed-point representations, but they can handle a larger range of numbers. Note that most floating-point numbers a computer can represent are just approximations. One of the difficulties in programming with floating-point values is ensuring that the approximations lead to reasonable results. Because mathematics with floating-point numbers requires a great deal of computing power, many microprocessors come with a chip, called a floating point unit (FPU), specialized for performing floating-point arithmetic. FPUs are also called math coprocessors and numeric coprocessors.

Since the earlier microprocessors didn't actually have any floating-point capabilities, they only dealt with integers. Floating-point calculations were done on separate, dedicated hardware, usually in the form of a math coprocessor. But when the integrated circuit chip technology began to sore, the computing industry found that the size of the transistor could be reduced - therefore more transistors could be etched onto the semi-conductor material inside of the physical chip. The decrease in transistor size permitted a floating-point unit directly on the main CPU die. Adding these units to the main CPU die (physical core that functions at the central processing unit) added hardware and floating point instructions into the mix. It would eventually introduce a set of extended (opcode) instructions called SIMD.

Today, modern microprocessors can execute the same instruction on multiple data. This is called Single Instruction Multiple Data (SIMD). SIMD instructions handle floating-point real numbers and also provide important speedups in algorithms. Because the execution units for SIMD instructions usually belong to a physical core, it is possible to run as many SIMD instructions in parallel as available physical cores. As mentioned, the usage of these vector-processing capabilities in parallel can provide important speedups in certain algorithms. The addition of SIMD instructions and hardware to a modern, multi-core CPU is a bit more drastic than the addition of floating point capability. Since their inception, a microprocessor is an SISD device (Single Instruction stream, Single Data stream).

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Finickiness of Craftwork

The receiver (Rx) coil for each application may have different geometries and/or power requirements. Since the Rx coil is a key component in a successful and efficient design of a Qi-compliant Rx and there are many design options and trade-offs to consider, the designer must take a careful and methodical approach when realizing a solution. This article provides the techni- cal insight needed to realize a successful Rx-coil design. It covers the Qi-compliant system model as a basic transformer; Rx-coil measurements and system-level influences; and methods of qualifying a design for successful operation.

Qi Compliance system modelling

For many near-field wireless power systems such as the one specified by the WPC, the behavior of the magnetic power transfer can be modeled by a simple transformer. A traditional transformer usually has a single physical structure with two windings around a core material that is highly permeable compared to air. Since the traditional transformer uses a highly permeable material to carry the magnetic flux, most (not all) of the flux produced by one coil couples to the second coil. This coupling, which can be measured through a parameter known as the coupling coefficient, is denoted as k (a measure that can have a value between 0 and 1).

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Time-Space

Succinctly put, if one has his plans going on, he won't give in to the pace and needs of people around. This would simply mean that he won't have much of moments and places shared with people... and no ideas too.

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Why We Are Moving to FinFET from Good Old MOSFET

Since the fabrication of MOSFET, the minimum channel length has been shrinking continuously. The motivation behind this decrease has been an increasing interest in high-speed devices and in very large-scale integrated circuits. The sustained scaling of conventional bulk device requires innovations to circumvent the barriers of fundamental physics constraining the conventional MOSFET device structure. The limits most often cited are control of the density and location of dopants providing high I on /I off ratio and finite sub threshold slope and quantum-mechanical tunneling of carriers through thin gate from drain to source and from drain to body.

The channel depletion width must scale with the channel length to contain the off-state leakage I off. This leads to high doping concentration, which degrade the carrier mobility and causes junction edge leakage due to tunneling. Furthermore, the dopant profile control, in terms of depth and steepness, becomes much more difficult. The gate oxide thickness tox must also scale with the channel length to maintain gate control, proper threshold voltage VT and performance. The thinning of the gate dielectric results in gate tunneling leakage, degrading the circuit performance, power and noise margin.

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Now Follows the Ivy Bridge!

Intel is the one who made first microprocessors, and yet Sandy Bridge could not match the competitors on graphics cores. 

The 22nm Ivy Bridge, although, has helped Intel grow some confidence in their designs.

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Where Does the Noice Come From in Analog Filters?

Article from EE Times:

Well, it turns out that things here don’t scale quite the way you might expect.

I’m going to concentrate on low-pass filters, whose noise bandwidths are essentially determined by their filter responses.

Active Noise: Some of it comes from the op amp(s). Each active filter topology has its inherent 'noise gain'. This shapes the inherent input voltage noise to be frequency-shaped in a way which is relate to--but not identical--to the actual shape of signal transfer function which the filter creates. This is of fundamental importance to all circuit designs: A circuit does not always process its internal noise the same way it processes the input noise(along with input signal) we apply.

Many op amps have not only an input voltage noise source, but a noise current source as well. The consequence is that any finite source impedance attached to an input of the filter’s amplifier, and therefore passing this noise current, creates an additional noise voltage that also contributes to the overall filter noise. Each topology again has its own signature here, also dependent on the apparent impedances of the resistor-capacitor networks that are hung on the amplifier.

Passive Noise--Capacitors & Johnson Noise: Last, but definitely not always least, is the fundamental noise contribution from the passive components themselves – resistors and capacitors, since we’re not considering any exotic active filters that include inductors. Now, there are two ways of looking at this noise that might seem to be diametrically opposed, but in fact spring from the same well of physical law.

One common perspective holds that Johnson noise in resistors is the only source of noise energy in a circuit, and that capacitors are noise-free and only affect circuit noise behavior through the interaction of their frequency-dependent impedances with the circuit resistances. Resistance to current flow is a bulk property of matter; anything made out of matter is at a non-zero absolute temperature, and hence the thermal energy in the structure of a resistor ‘smacks’ free charges around and causes a varying noise potential across any two points in the conductor. The contribution of the Johnson noise of each resistor in turn at the output is calculated using a linear AC analysis, and all the noises are squared and added. The square root of this sum is the overall rms total noise voltage.

we ignore the resistors and concentrate on the capacitors. The usual way of introducing this idea is to consider a resistor R and a capacitor C in parallel, and contemplate the noise voltage of the combination. The total noise voltage is the product of two pieces: the noise voltage density, which is proportional to sqrt(R), and the square root of the measurement bandwidth, which is proportional to 1/sqrt(RC). So the total noise is proportional to 1/sqrt(C) and the value of the resistor doesn’t even enter into it! As the resistor value changes, the spectral density of the noise changes, but the total integrated noise value is constant. This applies for arbitrarily high values of resistance, which of course result in arbitrarily low values of bandwidth, and noise voltages that could be moving very slowly indeed. This is not to say that capacitors actually generate noise. The residual uncertainty of the voltage on a capacitor in parallel with an infinitely large resistor (the combination hence having zero bandwidth) is an indication of the Johnson noise that it was exposed to at some time in the past, when the voltage was defined by contact with a circuit in which the resistance was finite. The capacitor has sampled the Johnson noise of the resistor in the circuit that charged it, and now it’s holding it for you. What’s interesting is that this behaviour generalizes to any RC network, including active ones. If we hold constant the capacitor values in an active filter, and scale the cutoff frequency with those resistors that determine it, the total noise contribution from the passive network stays constant.

When thinking about how noise levels can change as cutoff frequency choice is varied, the constant-capacitor approach feels more ‘fundamental’ than keeping the resistors constant and changing the capacitors (which would change the total noise). Knowing that the total noise is locked to a constant value takes one factor ‘out of the equation’ in your system design.

Of course, things get more complicated when you use a ‘real’ amplifier with its voltage and current noise contributions. Each term adds its own ‘footprint’ to the noise signature. The voltage noise of the amplifier creates a noise contribution whose value rises with the square root of the noise bandwidth it ‘sees’, which in turn is proportional to the filter’s cutoff frequency. Meanwhile the current noise at the amplifier inputs generates an equivalent voltage noise term that’s proportional to the impedance level, which is inversely proportional to cutoff frequency. So this contribution rises with falling cutoff frequency. The presence of 1/f noise in both the current and voltage terms creates yet more complexity. All these noise terms can be accommodated in the simple ‘universal opamp’ macromodel.

There’s indeed an ‘optimum’ cutoff frequency at which the total rms voltage noise is at a minimum.

About the author: Kendall Castor-Perry is a Principal Architect at Cypress Semiconductor,doing mixed-signal system analysis and design for the new PSoC platform.  Kendall uses decades of experience in analog engineering, filtering and signal processing to capture signals across many domains, extract the information from them and do something useful with it.

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Legacy Port

You know what is extremely inhuman about studying computer architecture? Same thing is being implemented in two very successful ways - Apple and PC, which must compel one to think there could be many more, and--well--better, ways to do it. Apple Desktop bus uses 4 pins while PS/2 uses 6: entirely different coding and mapping!

In computer engineering, microarchitecture, also called computer organization, is the way a given instruction set architecture (ISA) is implemented on a processor. A given ISA may be implemented with different microarchitectures. Implementations might vary due to different goals of a given design or due to shifts in technology.Computer architecture is the combination of microarchitecture and instruction set design.

In this article I am going to cover PS/2 first:

The PS/2 designs on keyboard and mouse interfaces are electrically similar and employ the same communication protocol. The PS/2 for mice and keyboards as 6 pins having male connectors. Mice and Keyboards have similar pins and same communication protocols which sometimes causes the microcontroller to be confused in case of any one malfunctioning.

Pin 1 +DATA Data Pin 2 Not connected Not connected* Pin 3 GND Ground Pin 4 Vcc +5 V DC at 275 mA Pin 5 +CLK Clock Pin 6 Not connected

Not connected**    

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Whif This Riff

A Perfect Circle, Opeth, AudioSlave, Tool, Pantera and Meshuggah in one playlist, that too at shuffle, and reading.

reading 4th PS2 communication data sheet; Jan Axelson - USB  Complete, 3 ed--second pdf being downloaded to Atlantis. Night & The Silent Waters, Opeth #nowplaying.

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Plastic Prototyping

Design is a matter of balance.

The Options In plastic part design, technology has given us a variety of prototyping options.  Rapid prototyping (RP) includes stereolithography, selective laser sintering, fused deposition modeling, laminated object manufacturing, and three dimensional printing.  Each of these builds parts, one-by-one, from 3D-CAD models, joining layers of material to create the finished prototype.  Rapid tooling (RT) uses rapid prototyping to create an initial part and then creates, from that part, a mold in which additional parts can be made.  Mold materials can range from silicone rubber to composites.  A third prototyping option is rapid injection molding (RIM), which works directly from a 3D-CAD model, using CNC machining to mill aluminum molds in which true injection-molded parts can be made.  Finally, there is traditional injection molding, which is used primarily for production, but could conceivably be used to create prototypes. 

Each method has strengths and weaknesses.

Rapid prototyping is the quickest, and can reproduce very complex shapes.  With no up-front tooling costs, it can be inexpensive as long as only a few parts are needed.  However, because each part is made from scratch, RP offers no economies of scale and its costs rise rapidly with quantity.  Parts can only be made from a limited range of materials and are typically left with a coarse finish. 

Rapid tooling can sometimes produce better quality parts than rapid prototyping, though materials choice is still somewhat limited.  It is also slower and more costly due to the extra step required to create a tool from the original prototype.  The need to create molds also increases up-front cost and can limit the complexity of shapes that can be effectively duplicated.

Rapid injection molding uses metal molds to produce truly functional parts with good finish and in a wide variety of resins.  It is similar to traditional injection molding (though far faster and much less costly). It is competitive with rapid tooling for speed and offers better economies of scale than rapid prototyping or rapid tooling. 

Traditional injection molding can produce the ultimate in part complexity and finish, but is generally considered too slow and expensive for prototyping, though it may be used when there is a high likelihood that the molds will go directly into large-scale production. 

Key Characteristics Characteristics of a prototype include quality, cost, and speed.  The required “quality” of a prototype can vary greatly.  In early design stages, the resemblance to a production part can be approximate, but as the process moves toward completion, the prototype must more closely match the finished part.  There are two measures of quality.  The first is form and fit – resemblance in shape, size, finish, and possibly even color to a production part.  The other is function – resemblance in strength, durability, chemical resistance, heat tolerance, and the like.