SOC System Design Approach

Introduction to the Systems
Approach
Mr. A. B. Shinde
Assistant Professor,
Electronics Engineering,
PVPIT, Budhgaon, Sangli
shindesir.pvp@gmail.com

System Architecture
• The term architecture denotes:
– The operational structure and
– The user’s view of the system.
• Over time, it has evolved to include
– Functional specification and
– Hardware implementation.
• The system architecture defines the system - level building blocks
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System Architecture: An Overview
3
The increasing transistor density on
a silicon die
The decrease of transistor cost
over the years

Components of the System
• Processors (core, multimedia & coprocessors)
• Memories (storing elements)
• Interconnects
4
A basic SOC system model

Hardware and Software
• Crucial decision to be made is:
1. Which components are to be implemented in hardware and
2. Which components are to be implemented in software.
• Software implementation usually uses general - purpose processor
(GPP), which interprets instructions at run time.
• This architecture offers flexibility and adaptability and provides a way
of sharing resources among different applications
• Hardware implementation of the ISA (Instruction Set Architecture) is
generally slower and consumes more power.
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6
 Most software developers use high - level languages and tools that
enhance productivity, such as program development environments,
optimizing compilers and performance profilers.
 Direct implementation of applications using hardware (ASICs), provides
high performance at the expense of programmability, flexibility,
productivity and cost.
Benefits Drawbacks
Hardware
Fast,
low power consumption
Inflexible,
unadaptable,
complex to build and test
Software
Flexible,
Adaptable,
simple to build and test
Slow,
high power consumption

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Programmability versus Performance
Coarse - Grained Reconfigurable Architecture
Application – Specific Instruction Processors

• Custom ASIC hardware and software on GPPs can be seen as two
extremes in the technology spectrum with different trade – offs
• An ASIP is a processor with an instruction set customized for a
specific application or domain.
• An FPGA typically contains an array of computation units, memories,
and their interconnections, all are programmable in the field by user.
• Because of the growing demand for reducing the time to market and
the increasing cost of chip fabrication, FPGAs are becoming more
popular for implementing digital designs.
• Coarse - Grained Reconfigurable Architecture (CGRA) It contains
logic blocks that process byte - wide or multiple byte - wide data,
which can form building blocks of datapaths.
• Structured ASIC It allows application builders to customize the
resources before fabrication. While it offers performance close to that
of ASIC.
• Digital Signal Processors (DSPs) The organization and instruction
set for these devices are optimized for digital signal processing
applications.
8

Processor Architectures
• Processors are characterized either by their application or by their
architecture (or structure)
9
Processors Identified by Function
Processors Identified by Architecture

Processor Architectures
• Sequential processors execute one instruction at a time.
• Many processors have the capability to execute several instructions
concurrently by means of pipelining, multiple execution units, and
multiple cores.
• Pipelining is a powerful technique.
• Instruction - level parallelism (ILP) means that multiple operations
can be executed in parallel within a program.
• ILP may be achieved with hardware, compiler, or operating system,
provided that there is no data dependency
• In general, a computer architecture consists of one or more
interconnected processor elements (PEs) that operate concurrently,
solving a single overall problem.
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Instruction - level parallelism (ILP)
• Instruction-level parallelism (ILP) is a measure of how many of the
operations in a computer program can be performed simultaneously.
Consider the following program:
• For Example:
1. e = a + b
2. f = c + d
3. g = e * f
Here, Operation 3 depends on the results of operations 1 and 2, so it
cannot be calculated until both of them are completed. As, operations
1 and 2 do not depend on any other operation, so they can be
calculated simultaneously.
If each operation is completed in one unit of time then three
instructions can be completed in two units of time, giving an ILP of 3/2.
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Processor: A Functional View
• Table shows different SOC designs and the processor used in each
design.
• For these examples, we can characterize them as general purpose, or
special purpose.
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Processor Models for Different SOC Examples

Processor: An Architectural View
• Simple Sequential Processor directly implement the sequential
execution model.
• The next instruction is not processed until all execution for the current
instruction is complete and its results have been committed.
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Instruction execution sequence.
1. IF - fetching the instruction into the instruction register (IF),
2. ID - decoding the opcode of the instruction (ID),
3. AG - generating the address in memory of any data item residing there,
4. DF - fetching data operands into executable registers (DF),
5. EX - executing the specified operation (EX), and
6. WB - writing back the result to the register file (WB).

• Sequential processor model
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During execution, a sequential processor executes one or more
operations per clock cycle from the instruction stream.
An instruction is a container that represents the smallest execution
packet managed explicitly by the processor.
Scalar and superscalar processors consume one or more instructions per
cycle, where each instruction contains a single operation.

• Pipelined Processor Pipelining is approach to exploit parallelism that
is based on concurrently performing different phases (instruction fetch,
decode, execution, etc.) of processing an instruction.
• Pipelining assumes that these phases are independent — when this
condition does not hold, the processor stalls the downstream phases
to enforce the dependency.
• Thus, multiple operations can be processed simultaneously with each
operation at a different phase of its processing.
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Instruction timing in a pipelined processor.

• Pipelined Processor
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Figure shows the general form of a pipelined processor.
Static pipeline, requires the processor to go through all stages or
phases of the pipeline.
Dynamic pipeline allows the bypassing of one or more pipeline
stages, depending on the requirements of the instruction.
The more complex dynamic pipelines allow instructions to complete out of
(sequential) order, or even to initiate out of order.

• When pipelining does not execute multiple instructions at exactly the
same time, there are other techniques to do the same.
• Most instructions consist of only a single operation, this kind of
parallelism has been named ILP (instruction level parallelism).
• Two architectures that exploit (implement) ILP are superscalar and
VLIW (Very Long Instruction Word) processors.
• A superscalar processor dynamically examines the instruction
stream to determine which operations are independent and can be
executed.
• A VLIW processor relies on the compiler to analyze the available
operations (OP) and to schedule independent operations into wide
instruction words.
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• Figure shows the instruction timing of a pipelined superscalar or
VLIW processor executing two instructions per cycle.
• In this case, all the instructions are independent so that they can be
executed in parallel.
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• Superscalar Processors:
• Dynamic pipelined processors has limitations to execute a single
operation per cycle.
• This limitation can be avoided with the addition of multiple
functional units and a dynamic scheduler to process more than one
instruction per cycle.
• Superscalar processors can achieve execution rates of several
instructions per cycle (usually limited to two, but more is possible
depending on the application).
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Superscalar processor model

• Superscalar Processors:
• A superscalar processor adds a scheduling instruction window that
analyzes multiple instructions from the instruction stream in each
cycle.
• These instructions are treated in the same manner as in a pipelined
processor.
• Because of the complexity of the dynamic scheduling logic, high –
performance superscalar processors are limited to processing
four to six instructions per cycle.
• In Flynn's taxonomy, a single-core superscalar processor is
classified as an SISD processor whereas a multi-core superscalar
processor is classified as an MIMD processor
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• VLIW (Very Long Instruction Word) Processors
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In contrast to dynamic analysis in hardware to determine which
operations can be executed in parallel, VLIW processors rely on static
analysis in the compiler
VLIW processor model

• VLIW processors are less complex than superscalar processors and
have the potential for higher performance.
• A VLIW processor executes operations from statically scheduled
instructions.
• VLIW processors rely on the static analysis performed by the
compiler and are unable to take advantage of any dynamic
execution characteristics.
• A simple VLIW implementation results in high performance.
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• VLIW processors:
• VLIW instruction encodes multiple operations, at least one
operation for each execution unit of a device.
• For example, if a VLIW device has four execution units, then a
VLIW instruction for the device has four operation fields, each field
specifying what operation should be done on that corresponding
execution unit.
• To accommodate these operation fields, VLIW instructions are usually
at least 64 bits wide, and far wider on some architectures.
• For example:
• In one cycle, it does a floating-point multiply, a floating-point add, and
two auto increment loads. All of this fits in one 48-bit instruction:
f12 = f0 * f4, f8 = f8 + f12, f0 = dm(i0, m3), f4 = pm(i8, m9);
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• SIMD Architectures:
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• SIMD Architectures:
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SIMD Processable Patterns SIMD Unprocesable Patterns
Example: Brightness Computation by SIMD Operations

• SIMD Architectures: Array and Vector Processors:
• The SIMD class of processor architecture includes both array and
vector processors.
• From the view of an assembly - level programmer, programming
SIMD architecture appears to be similar to programming a simple
processor.
27

• SIMD Architectures: Array and Vector Processors:
• The two popular types of SIMD processor are the array processor
and the vector processor.
• They differ both in their implementations and in their data
organizations.
• An array processor consists of many interconnected processor
elements, each having their own local memory space.
• A vector processor consists of a single processor that references a
global memory space and has special function units that operate
on vectors.
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• Array processor
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Array processor model.
Array processor: Is a set of parallel processor elements connected via
one or more networks, possibly including local and global inter element
communications and control communications.
Each processor element (PE) has its own private memory.
Data is distributed across the elements in a regular fashion… i.e. dependent
on both the actual structure of the data and also the computations to be
performed on the data.

• Array processor:
• Direct access to global memory or another processor element’s
local memory is expensive, so intermediate values are propagated
through the array through local inter-processor connections.
• Since instructions are broadcast, processor element cannot alter
the flow of the instruction stream;
however, individual processor elements can conditionally
disable instructions based on local status information i.e. processor
elements remains idle.
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• The actual instruction stream consists of more than a fixed stream
of operations.
• An array processor is typically coupled to a general - purpose
control processor that provides both scalar operations as well as
array operations that are broadcasted to all processor elements in
the array.
• The control processor performs the scalar sections of the
application, interfaces with the outside world, and controls the
flow of execution;
• The array processor performs the array sections of the application
as directed by the control processor.
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• Vector Processors:
• A vector processor is a single processor that resembles a
traditional single stream processor, except that some of the functional
units (and registers) operate on vectors (sequences of data values).
• These functional units are deeply pipelined and have high clock
rates.
• The vector pipelines often have the rapid delivery of the input
vector data elements, together with the high clock rates, results in a
significant throughput.
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Vector processor model.

• A typical vector processor configuration consists of:
a vector register file,
one vector addition unit,
one vector multiplication unit, and
one vector reciprocal unit (used along with the vector multiplication unit to
perform division)
35
Vector processor model.

• In modern vector processors, vectors are loaded into special vector
registers and stored back into memory
• Vector processors have several features that enable them to achieve
high performance.
• One of the feature is, the ability to concurrently load and store
values between the vector register file and the main memory while
performing computations on values in the vector register file.
• If the length of vector register is limited and vectors longer than
the register length needs to be processed then they are processed
in segments.
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• Most vector processors support a result bypassing:
— that allows a follow - on computation to commence as soon as
the first value is available from the preceding computation.
Thus, instead of waiting for the entire vector to be processed, the
follow - on computation can be significantly overlapped with the
preceding computation that it is dependent on.
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Memory and Addressing
• Memory requirements in SOC applications varies significantly.
• In one case, the memory program can reside entirely in an on-chip
ROM, with the data in on-chip RAM.
• In another case, the memory system might support an elaborate
operating system requiring a large off-chip memory (system on a
board), with a memory management unit and cache.
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• Why not simply include memory with the processor on the die?
• This has many attractions
(Benefits of embedding memory & processor on same die):
1. It improves the accessibility of memory, improving both memory
access time and bandwidth.
2. It reduces the need for large cache.
3. It improves performance for memory based applications.
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• Drawbacks of embedding memory & processor on same die:
• First problem is that DRAM memory process technology differs
from standard microprocessor process technology, and would
cause some sacrifice in achievable bit density.
• Second problem is more serious: If memory were restricted to the
processor die, its size would be correspondingly limited.
• Thus, the conventional processor die model has evolved to implement
multiple robust homogeneous processors sharing the higher levels of
a two or three-level cache structure with the main memory off-die, on
its own multi die module.
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• From a design complexity point of view, this has the advantage of
being a ― universal ‖ solution: One implementation fits all
applications, although not necessarily equally well.
• So, the production quantities can be large enough to justify the
costs.
41

• An alternative to the previous approach is integrate the memory on
system die.
• For specific applications, whose memory size can be bounded, we can
implement an integrated memory SOC. This concept is illustrated in
above figure
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• SOC Memory Examples
• It is important for SOC designers to consider whether to put RAM and
ROM on-die or off-die.
• Table shows various examples of SOC embedded memory macro cell.
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SOC Memory
Considerations

• Addressing: The Architecture of Memory
• Addressing facilities are available to the programmer.
• Some facilities are available to the application programmer and
some to the operating system programmer.
• Virtual memory enables programs requiring larger storage than
the physical memory.
• When virtual addressing facilities are properly implemented and
programmed, memory can be efficiently and securely accessed.
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• Virtual memory is often supported by a memory management unit.
• The physical memory address is determined by a sequence of (at
least) three steps:
1. The application produces a process address, this together with the
process or user ID, defines the virtual address:
virtual address = offset + (program) base + index ,
where the offset is specified in the instruction while the base and
index values are in specified registers.
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least) three steps:
2. Since multiple processes must cooperate in the same memory space,
the process addresses must be coordinated and relocated.
This is typically done by a segment table.
Upper bits of the virtual address are used to address a segment
table.
system address = virtual address + (process) base
where the system address must be less than the bound .
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least) three steps:
3. Virtual versus real. For many SOC applications, the memory space
exceeds the available (real) implemented memory.
Memory space is implemented on disk and only the recently used
regions (pages) are brought into memory.
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System - Level Interconnection
• SOC technology typically relies on the interconnection of
predesigned circuit modules (known as intellectual property (IP)
blocks) to form a complete system.
• In this way, the design task is raised from a circuit level to a system
level.
• Central to the system – level performance and the reliability of the
finished product is dependent on the method of interconnection used.
• A well - designed interconnection scheme should have efficient
communication protocols
48

• It should provide efficient communication between different modules
maximizing the degree of parallelism.
• SOC interconnect methods can be classified into two main
approaches: buses and network - on - chip,
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• Bus - Based Approach
50
With the bus - based approach, IP blocks are designed to conform to published bus
standards (AMBA or CoreConnect).
Communication between modules is achieved through the sharing of the physical
connections of address, data, and control bus signals.
Usually, two or more buses are employed in a system, organized in a hierarchical
fashion.
To optimize system - level performance and cost, the bus closest to the CPU has the
highest bandwidth, and the bus farthest from the CPU has the lowest bandwidth.

• Network - on - Chip Approach
51
A network - on - chip system consists of an
array of switches, either dynamically
switched as in a crossbar or statically
switched as in a mesh.
The crossbar approach uses
asynchronous channels to connect
synchronous modules that can operate at
different clock frequencies.
This approach has the advantage of higher
throughput than a bus - based system
while making integration of a system with
multiple clock domains easier.

• Network - on - Chip Approach
52
This interconnect scheme is based on a
two - dimensional mesh topology.
All communications between switches
are conducted through data packets,
routed through the router interface circuit
within each node.
Since the interconnections between
switches have a fixed distance,
interconnect - related problems such as
wire delay and cross talk noise are much
reduced.

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Interconnect Models for Different SOC Examples

An Approach For Soc Design
• Two important ideas in a design process are:
1. Figuring out the requirements and specifications, and
2. Iterating through different stages of design toward an efficient and
effective completion.
• Requirements and Specifications
• Design Iteration
– Initial Design
– Optimized Design
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• Requirements and Specifications :
• There must be a deep understanding before a starting of design
process.
• They are useful at the beginning and at the end of the design process:
– At the beginning, to clarify what needs to be achieved; and
– At the end, as a reference against which the completed design
can be evaluated.
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• The system requirements are the externally generated criteria for
the system.
• They may come from competition, from sales insights, from
customer requests, from product profitability analysis, or from a
combination of all.
• Requirements are rarely definitive of anything about the system.
Indeed, requirements can frequently be unrealistic:
“I want it fast, I want it cheap, and I want it now ”
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• It is important for the designer to analyze carefully the
requirements, expressions, and to spend sufficient time in
understanding the market situation to determine all the factors
expressed in the requirements.
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• Some of the factors the designer considers in determining
requirements include
• Compatibility with previous designs or published standards,
• Reuse of previous designs,
• Customer requests/complaints,
• Sales reports,
• Cost analysis,
• Competitive equipment analysis, and
• Trouble reports (reliability) of previous products and
competitive products.
58

• Design Iteration:
• Design is always an iterative process.
• So, the obvious question is how to get the very first, initial design?
• This is the design that we can then iterate through and optimize
according to the design criteria.
59

• Initial Design:
• This is the first design that meets
the key requirements, while other
performance and cost criteria’s
are not considered.
• For instance, processor or
memory or input/output (I/O)
should be sized to meet all (high
– priority, real – time) constraints.
• Promising components and their
parameters are selected for
better performance.
• It is simplified model of the
expected computational capacity
or data bandwidth capability.
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The SOC initial design process

• Optimized Design:
• Once the base performance (or area) requirements are met and the
base functionality is ensured, then the goal is to minimize:
– the cost (area) and/or
– the power consumption or
– the design effort required to complete the design.
• This is the iterative step of the process.
• The first steps of this process use higher - fidelity tools (simulations,
trial layouts, etc.) to ensure that the initial design actually does satisfy
the design specifications and requirements.
• The later steps refine, complete, and improve the design according to
the design criteria.
61

System Architecture and Complexity
• The basic difference between processor architecture and system
architecture is that the system adds another layer of complexity, and
the complexity of these systems limits the cost savings.
• Historically, the computer is a single processor plus a memory.
• As long as this is fixed (within broad tolerances), implementing that
processor on one or more silicon die does not change the design
complexity.
• Once die densities enable a scalar processor to fit on a chip, the
complexity issue changes.
62

• As transistor densities significantly improve after this point, there are
obvious processor extension strategies to improve performance:
1. Additional Cache: Here we add cache storage and, as large
caches have slower access times, a second - level cache.
2. A More Advanced Processor: We implement a superscalar or a
VLIW processor that executes more than one instruction each cycle.
Additionally, we can speed up the execution units that affects the
critical path delay, especially the floating - point execution times.
3. Multiple Processors: Now we implement multiple (superscalar)
processors and their associated multilevel caches.
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• Instead of the 100,000
transistor processors, our
advanced processor has
millions of transistors.
• The way to manage this
complexity is to reuse
designs.
• So, reusing several simpler
processor designs
implemented on a die is
preferable to a new, more
advanced, single
processor.
• For this to work, we need a
good interconnection
mechanism to access the
various processors and
memory.
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Complexity of design

• So, when an application is well specified, the system-on-a-chip
approach includes
1. Multiple (usually) heterogeneous processors, each specialized for
specific parts of the application;
2. The main memory with (often) ROM for partial program storage;
3. A relatively simple, small (single - level) cache structure or
buffering schemes associated with each processor; and
4. A bus or switching mechanism for communications.
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Product Economics And Implications For SoC
• Factors Affecting
Product Costs
• The basic cost and
profitability of a product
depend on many factors:
• its technical appeal,
• its cost,
• the market size, and
• the effect the product
has on future products.
• The issue of cost goes well
beyond the product’s
manufacturing cost.
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Project cost components

• Factors Affecting Engineering Costs
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• Modelling Product Economics and Technology Complexity
• To put all this into perspective, consider a general model of a product’s
average unit cost:
unit cost = (project cost) / (number of units).
• The product cost is simply the sum of all the fixed and variable costs.
• We represent the fixed cost as a constant, Kf .
• It is also clear that the variable costs are of the form Kv × n , where n is
the number of units.
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Thank You…
This presentation is published only for Educational Purpose
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SOC System Design Approach

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SOC System Design Approach