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Chapt.2 Machine Architecture

Chapt.2 Machine Architecture

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Chapt.2 Machine Architecture

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  1. Chapt.2 Machine Architecture • Impact of languages • Support – faster, more secure • Primitive Operations • e.g. nested subroutine calls • Subroutines implemented with stack (ex: PL/1- recursion) • IBM704 – index registers • Security • e.g., data and code kept separate • O.S. kept separate • Limitations • Space • Time • Networks, multiprocessors, etc.

  2. Hardware or actual computer • Data / storage CELL • Main memory, cache and registers • Fixed-length words determines range of values of data • Limitation on range and precision of numbers • Strictly speaking, built-in types are determined by operations • Operations on data • Primitive operations manipulate data • Integer, character, bit string, (1-dimensional) arrays • Possibly floating-point, character string • Data operations are valid on all data cells

  3. Hardware • Sequence control (control operations) • Sequence (von Neumann architecture) • Program address register (PC) incremented automatically • Jump or branch • Branch conditionally • Multiprocessing as alternative control mechanism • Data access • Operation (move, load, etc.) • Operand – typically address of cell • RISC (fewer hardware ops) vs CISC

  4. Hardware • Effect of current access times • Register access – 5-10 nsec • Memory access – 50-70 nsec • I/O access – 10-15 msec. • Modular programs can make efficient use of cache and virtual memory (hits) • Cost of tasking • In-line modules • Multi-dimensional arrays

  5. Computer states • State transitions for representing virtual machine • State transition diagrams for proving correctness

  6. Role of firmware • Instructions in microprogram • Emulation to create virtual computer • FORTRAN hardware machine • Statements in hardware/firmware • Translator is interpreter • Cost in terms of flexibility, monetary, speed • Slower for running spreadsheet, for example

  7. Translators • Translators allow for the creation of virtual machines • A program language defines its own machine • May restrict data operations • e.g., pure LISP does not have use floating point operations • May restrict control operations • Typically does not allow use of primitive i/o operations • Adds its own data and control structures

  8. Translators • Interpreter – decodes and executes each hardware machine instruction or higher level statement (initially Basic, Snobol, LISP, Perl, Smalltalk, Java) • Does not create object code • Each statement (even in a loop) must be repeatedly translated • Assembler – specific to hardware; translates almost 1-1 to hardware machine instruction

  9. Translators • Virtual machine is portable, user friendly(?) • Compiler creates object code in assembler or hardware machine language • Quick and dirty • Optimizing • Cross compiler – translates to machine language of another machine (simulation) • Useful for designing code for small chips • Load or link editor - source code is typically relocatable and object code is a single executable program with external references resolved • Preprocessor or macroprocessor • Source and object code both in high level language • Initial pass for expanding macros, constants, C++, etc.

  10. Hierarchies of virtual machines • Hardware machine- gates, switches • Augmented by microcode • Operating System virtual machine • Denies some functions • Adds some capabilities • e.g., i/o, semaphores • C virtual computer • Hides/ adds capabilities • C library routines • Web virtual machine • Browser executing HTML, XML pages

  11. Binding Times • Binding of data: association with cell(s) • Binding of operation: association with hardware primitive operation(s) • Typically several intermediate steps • Flexibility versus efficiency/ reliability • Late binding provides greater flexibility, less efficiency, typically less reliability

  12. Binding Times • During program execution • Module entry- semi-dynamic • Arbitrary run times – dynamic • During compile/ translation time • Bindings chosen by the programmer • Ex: types and their operations • Array and record size • Bindings chosen by the translator • Ex: position of data on the stack • Bindings chosen by the loader, linker • Ex: storage location or displacement

  13. Binding Times • During language implementation for specific hardware • possibly number implementation • C’s int • Issue of portability • During language definition type • The ability to define more operations for a type • The ability to define new data types

  14. Binding Times: example • Statement X = X + 10 • Association of Type with X • Language definition determines possible range of types (int, short int, float, complex, user defined, etc.) • X’s type may be chosen statically (C), or dynamically (SNOBOL) • Association of Value with X • Language implementation may determine range and representation of value • X’s value is determined at arbitrary pts of execution • Association of + • Language definition determines what + can be (or sum, etc.) • Binding of + to hardware or software op • Compile time in FORTRAN, C • At arbitrary pts of execution in C++ – polymorphism

  15. Binding time: example • static int X = 10; • In C • X’s range of types, meaning of = are determined at language definition • X is assigned 10 only upon first execution • X retains value between calls

  16. Do we need to know about the hardware? • High speed, large memories shield us from many of the problems that earlier programmers had • Speed of translating and executing Java is small in relation to network transmission, user response time • Can careful language design shield us from hardware? – not entirely