In computer science, threaded code is a programming technique where the code has a form that essentially consists entirely of calls to subroutines. It is often used in compilers, which may generate code in that form or be implemented in that form themselves. The code may be processed by an interpreter or it may simply be a sequence of machine code call instructions.
Threaded code has better density than code generated by alternative generation techniques and by alternative calling conventions. In cached architectures, it may execute slightly slower.[ citation needed ] However, a program that is small enough to fit in a computer processor's cache may run faster than a larger program that suffers many cache misses. Small programs may also be faster at thread switching, when other programs have filled the cache.
Threaded code is best known for its use in many compilers of programming languages, such as Forth, many implementations of BASIC, some implementations of COBOL, early versions of B, [ citation needed ]and other languages for small minicomputers and for amateur radio satellites.
This section possibly contains original research . (February 2020) (Learn how and when to remove this template message)
The common way to make computer programs is to use a compiler to translate source code (written in some symbolic language) to machine code. The resulting executable is typically fast but, because it is specific to a hardware platform, it isn't portable. A different approach is to generate instructions for a virtual machine and to use an interpreter on each hardware platform. The interpreter instantiates the virtual machine environment and executes the instructions. Thus, only the interpreter must be compiled.
Early computers had relatively little memory. For example, most Data General Nova, IBM 1130, and many of the first microcomputers had only 4 kB of RAM installed. Consequently, a lot of time was spent trying to find ways to reduce a program's size, to fit in the available memory.
One solution is to use an interpreter which reads the symbolic language a bit at a time, and calls functions to perform the actions. As the source code is typically much denser than the resulting machine code, this can reduce overall memory use. This was the reason Microsoft BASIC is an interpreter: kB memory of machines like the Altair 8800 with the user's source code. A compiler translates from a source language to machine code, so the compiler, source, and output must all be in memory at the same time. In an interpreter, there is no output. Code is created a line at a time, executed, and then discarded.its own code had to share the 4
Threaded code is a formatting style for compiled code that minimizes memory use. Instead of writing out every step of an operation at its every occurrence in the program, as was common in macro assemblers for instance, the compiler writes each common bit of code into a subroutine. Thus, each bit exists in only one place in memory (see "Don't repeat yourself"). The top-level application in these programs may consist of nothing but subroutine calls. Many of these subroutines, in turn, also consist of nothing but lower-level subroutine calls. This technique — code refactoring — remains widely used today, although for different reasons.
Mainframes and some early microprocessors such as the RCA 1802 required several instructions to call a subroutine. In the top-level application and in many subroutines, that sequence is constantly repeated, with only the subroutine address changing from one call to the next. This means that a program consisting of many function calls may have considerable amounts of repeated code as well.
To address this, threaded code systems used pseudo-code to represent function calls in a single operator. At run time, a tiny "interpreter" would scan over the top-level code, extract the subroutine's address in memory, and call it. In other systems, this same basic concept is implemented as a branch table, dispatch table, or virtual method table, all of which consist of a table of subroutine addresses.
During the 1970s, hardware designers spent considerable effort to make subroutine calls faster and simpler. On the improved designs, only a single instruction is expended to call a subroutine, so the use of a pseudo-instruction saves no room.[ citation needed ] Additionally, the performance of these calls is almost free of additional overhead. Today, though almost all programming languages focus on isolating code into subroutines, they do so for code clarity and maintainability, not to save space.
Threaded code systems save room by replacing that list of function calls, where only the subroutine address changes from one call to the next, with a list of execution tokens, which are essentially function calls with the call opcode(s) stripped off, leaving behind only a list of addresses.
Over the years, programmers have created many variations on that "interpreter" or "small selector". The particular address in the list of addresses may be extracted using an index, general purpose register or pointer. The addresses may be direct or indirect, contiguous or non-contiguous (linked by pointers), relative or absolute, resolved at compile time or dynamically built. No single variation is "best" for all situations.
To save space, programmers squeezed the lists of subroutine calls into simple lists of subroutine addresses, and used a small loop to call each subroutine in turn. For example, the following pseudocode uses this technique to add two numbers A and B. In the example, the list is labeled thread and a variable ip (Instruction Pointer) tracks our place within the list. Another variable sp (Stack Pointer) contains an address elsewhere in memory that is available to hold a value temporarily.
start:ip=&thread// points to the address '&pushA', not the textual label 'thread'top:jump*ip++// follow ip to address in thread, follow that address to subroutine, advance ipthread:&pushA&pushB&add...pushA:*sp++=A// follow sp to available memory, store A there, advance sp to next jumptoppushB:*sp++=Bjumptopadd:addend=*--sp// point sp to last value saved on stack, follow it to copy that value out*sp++=*--sp+addend// copy another value out of stack, add, copy sum into stackjumptop
The calling loop at
top is so simple that it can be repeated inline at the end of each subroutine. Control now jumps once, from the end of a subroutine to the start of another, instead of jumping twice via
top. For example:
start:ip=&thread// ip points to &pushA (which points to the first instruction of pushA)jump*ip++// send control to first instruction of pushA and advance ip to &pushBthread:&pushA&pushB&add...pushA:*sp++=A// follow sp to available memory, store A there, advance sp to next jump*ip++// send control where ip says to (i.e. to pushB) and advance ippushB:*sp++=Bjump*ip++add:addend=*--sp// point sp to last value saved on stack, follow it to copy that value out*sp++=*--sp+addend// copy another value out of stack, add, copy sum into stackjump*ip++
This is called direct threaded code (DTC). Although the technique is older, the first widely circulated use of the term "threaded code" is probably James R. Bell's 1973 article "Threaded Code".
In 1970, Charles H. Moore invented a more compact arrangement, indirect threaded code (ITC), for his Forth virtual machine. Moore arrived at this arrangement because Nova minicomputers had an indirection bit in every address, which made ITC easy and fast. Later, he said that he found it so convenient that he propagated it into all later Forth designs.
Today, some Forth compilers generate direct-threaded code while others generate indirect-threaded code. The executables act the same either way.
Practically all executable threaded code uses one or another of these methods for invoking subroutines (each method is called a "threading model").
Addresses in the thread are the addresses of machine language. This form is simple, but may have overheads because the thread consists only of machine addresses, so all further parameters must be loaded indirectly from memory. Some Forth systems produce direct-threaded code. On many machines direct-threading is faster than subroutine threading (see reference below).
An example of a stack machine might execute the sequence "push A, push B, add". That might be translated to the following thread and routines, where
ip is initialized to the address labeled
thread (i.e., the address where
&pushA is stored).
start:ip=&thread// ip points to &pushA (which points to the first instruction of pushA)jump*ip++// send control to first instruction of pushA and advance ip to &pushBthread:&pushA&pushB&add...pushA:*sp++=Ajump*ip++// send control where ip says to (i.e. to pushB) and advance ippushB:*sp++=Bjump*ip++add:addend=*--sp*sp++=*--sp+addendjump*ip++
Alternatively, operands may be included in the thread. This can remove some indirection needed above, but makes the thread larger:
start:ip=&threadjump*ip++thread:&push&A// address where A is stored, not literal A&push&B&add...push:*sp++=*ip++// must move ip past operand address, since it is not a subroutine addressjump*ip++add:addend=*--sp*sp++=*--sp+addendjump*ip++
Indirect threading uses pointers to locations that in turn point to machine code. The indirect pointer may be followed by operands which are stored in the indirect "block" rather than storing them repeatedly in the thread. Thus, indirect code is often more compact than direct-threaded code. The indirection typically makes it slower, though usually still faster than bytecode interpreters. Where the handler operands include both values and types, the space savings over direct-threaded code may be significant. Older FORTH systems typically produce indirect-threaded code.
For example, if the goal is to execute "push A, push B, add", the following might be used. Here,
ip is initialized to address
&thread, each code fragment (
add) is found by double-indirecting through
ip and an indirect block; and any operands to the fragment are found in the indirect block following the fragment's address. This requires keeping the current subroutine in
ip, unlike all previous examples where it contained the next subroutine to be called.
start:ip=&thread// points to '&i_pushA'jump*(*ip)// follow pointers to 1st instruction of 'push', DO NOT advance ip yetthread:&i_pushA&i_pushB&i_add...i_pushA:&push&Ai_pushB:&push&Bi_add:&addpush:*sp++=*(*ip+1)// look 1 past start of indirect block for operand addressjump*(*++ip)// advance ip in thread, jump through next indirect block to next subroutineadd:addend=*--sp*sp++=*--sp+addendjump*(*++ip)
So-called "subroutine-threaded code" (also "call-threaded code") consists of a series of machine-language "call" instructions (or addresses of functions to "call", as opposed to direct threading's use of "jump"). Early compilers for ALGOL, Fortran, Cobol and some Forth systems often produced subroutine-threaded code. The code in many of these systems operated on a last-in-first-out (LIFO) stack of operands, for which compiler theory was well-developed. Most modern processors have special hardware support for subroutine "call" and "return" instructions, so the overhead of one extra machine instruction per dispatch is somewhat diminished.
Anton Ertl, the Gforth compiler's co-creator, stated that "in contrast to popular myths, subroutine threading is usually slower than direct threading".However, Ertl's most recent tests show that subroutine threading is faster than direct threading in 15 out of 25 test cases. More specifically, he found that direct threading is the fastest threading model on Xeon, Opteron, and Athlon processors, indirect threading is fastest on Pentium M processors, and subroutine threading is fastest on Pentium 4, Pentium III, and PPC processors.
As an example of call threading for "push A, push B, add":
Token-threaded code uses lists of 8 or 12-bit [ citation needed ] indexes to a table of pointers. It is notably compact, without much special effort by a programmer. It is usually half to three-fourths the size of other threadings, which are themselves a quarter to an eighth the size of non-threaded code. The table's pointers can either be indirect or direct. Some Forth compilers produce token-threaded code. Some programmers consider the "p-code" generated by some Pascal compilers, as well as the bytecodes used by .NET, Java, BASIC and some C compilers, to be token-threading.
A common approach, historically, is bytecode, which uses 8-bit opcodes and, often, a stack-based virtual machine. A typical interpreter is known as a "decode and dispatch interpreter", and follows the form:
start:vpc=&threadtop:i=decode(vpc++)/* may be implemented simply as: return *vpc */addr=table[i]jump*addrthread:/* Contains bytecode, not machine addresses. Hence it is more compact. */1/*pushA*/2/*pushB*/0/*add*/table:&add/* table = address of machine code that implements bytecode 0 */&pushA/* table ... */&pushB/* table ... */pushA:*sp++=AjumptoppushB:*sp++=Bjumptopadd:addend=*--sp*sp++=*--sp+addendjumptop
If the virtual machine uses only byte-size instructions,
decode() is simply a fetch from
thread, but often there are commonly used 1-byte instructions plus some less-common multibyte instructions (see complex instruction set computer), in which case
decode() is more complex. The decoding of single byte opcodes can be very simply and efficiently handled by a branch table using the opcode directly as an index.
For instructions where the individual operations are simple, such as "push" and "add", the overhead involved in deciding what to execute is larger than the cost of actually executing it, so such interpreters are often much slower than machine code. However, for more complex ("compound") instructions, the overhead percentage is proportionally less significant.
Counter-intuitively, token-threaded code can sometimes run faster than the equivalent machine code -- when the machine code is too large to fit in cache, but the higher code density of threaded code, especially token-threaded code, allows it to fit entirely in high-speed cache.
Huffman threaded code consists of lists of tokens stored as Huffman codes. A Huffman code is a variable-length string of bits that identifies a unique token. A Huffman-threaded interpreter locates subroutines using an index table or a tree of pointers that can be navigated by the Huffman code. Huffman-threaded code is one of the most compact representations known for a computer program. The index and codes are chosen by measuring the frequency of calls to each subroutine in the code. Frequent calls are given the shortest codes. Operations with approximately equal frequencies are given codes with nearly equal bit-lengths. Most Huffman-threaded systems have been implemented as direct-threaded Forth systems, and used to pack large amounts of slow-running code into small, cheap microcontrollers. Most publisheduses have been in smart cards, toys, calculators, and watches. The bit-oriented tokenized code used in PBASIC can be seen as a kind of Huffman-threaded code.
An example is string threading, in which operations are identified by strings, usually looked up by a hash table. This was used in Charles H. Moore's earliest Forth implementations and in the University of Illinois's experimental hardware-interpreted computer language. It is also used in Bashforth.
HP's RPL, first introduced in the HP-18C calculator in 1986, is a type of proprietary hybrid direct-threaded and indirect-threaded threaded-interpreted language that, unlike others TILs, allows embedding of RPL "objects" into the "runstream" ie. The stream of addresses through which the interpreter pointer advances. An RPL "object" can be thought of as a special data type whose in-memory structure contains an address to an "object prolog" at the start of the object, and then data or executable code follows. The object prolog determines how the object's body should be executed or processed. Using the "RPL inner loop" :, which was invented and published ( and patented ) by William C. Wickes in 1986 and published in "Programming Environments", Institute for Applied Forth Research, Inc., 1988, execution follows like so
This can represented more precisely by :
O = [I] I = I + Δ PC = [O] + Δ
Where above, O is the current object pointer, I is the interpreter pointer, Δ is the length of one address word and the "" operator stands for "dereference".
When control is transferred to an object pointer or an embedded object, execution continues as follows :
PROLOG -> PROLOG ( The prolog address at the start of the prolog code points to itself ) IF O + Δ =/= PC THEN GOTO INDIRECT ( Test for direct execution ) O = I - Δ ( Correct O to point to start of embedded object ) I = I + α ( Correct I to point after embedded object where α is the length of the object ) INDIRECT ( rest of prolog )
On HP's Saturn microprocessors that use RPL, there is a third level of indirection made possible by an architectural / programming trick which allows faster execution.
In all interpreters, a branch simply changes the thread pointer (
ip above). A conditional branch, to jump if the top-of-stack value is zero, might be encoded as follows. Note that
&thread is the location to which to jump, not the address of a handler. So, it must be skipped (
ip++) regardless of whether the branch is taken.
Separating the data and return stacks in a machine eliminates a great deal of stack management code, substantially reducing the size of the threaded code. The dual-stack principle originated three times independently: for Burroughs large systems, Forth, and PostScript. It is used in some Java virtual machines.
Three registers are often present in a threaded virtual machine. Another one exists for passing data between subroutines ('words'). These are:
Often, threaded virtual machines, such as implementations of Forth, have a simple virtual machine at heart, consisting of three primitives. Those are:
In an indirect-threaded virtual machine, the one given here, the operations are:
This is perhaps[ citation needed ] the simplest and fastest interpreter or virtual machine.
Forth is an imperative stack-based computer programming language and environment originally designed by Chuck Moore. Language features include structured programming, reflection, concatenative programming and extensibility. Although not an acronym, the language's name is sometimes spelled with all capital letters as FORTH, following the customary usage during its earlier years.
In computer programming, machine code, consisting of machine language instructions, is a low-level programming language used to directly control a computer's central processing unit (CPU). Each instruction causes the CPU to perform a very specific task, such as a load, a store, a jump, or an arithmetic logic unit (ALU) operation on one or more units of data in the CPU's registers or memory.
In computer programming, a p-code machine, or portable code machine is a virtual machine designed to execute p-code. This term is applied both generically to all such machines, and to specific implementations, the most famous being the p-Machine of the Pascal-P system, particularly the UCSD Pascal implementation.
Common Intermediate Language (CIL), formerly called Microsoft Intermediate Language (MSIL) or Intermediate Language (IL), is the intermediate language binary instruction set defined within the Common Language Infrastructure (CLI) specification. CIL instructions are executed by a CLI-compatible runtime environment such as the Common Language Runtime. Languages which target the CLI compile to CIL. CIL is object-oriented, stack-based bytecode. Runtimes typically just-in-time compile CIL instructions into native code.
In computer science, an interpreter is a computer program that directly executes instructions written in a programming or scripting language, without requiring them previously to have been compiled into a machine language program. An interpreter generally uses one of the following strategies for program execution:
The Intel MCS-51 is a single chip microcontroller (MCU) series developed by Intel in 1980 for use in embedded systems. The architect of the Intel MCS-51 instruction set was John H. Wharton. Intel's original versions were popular in the 1980s and early 1990s and enhanced binary compatible derivatives remain popular today. It is an example of a complex instruction set computer, and has separate memory spaces for program instructions and data.
x86 Assembly Language is a family of backward-compatible assembly languages, which provide some level of compatibility all the way back to the Intel 8008 introduced in April 1972. x86 assembly languages are used to produce object code for the x86 class of processors. Like all assembly languages, it uses short mnemonics to represent the fundamental instructions that the CPU in a computer can understand and follow. Compilers sometimes produce assembly code as an intermediate step when translating a high level program into machine code. Regarded as a programming language, assembly coding is machine-specific and low level. Assembly languages are more typically used for detailed and time critical applications such as small real-time embedded systems or operating system kernels and device drivers.
In computer science, a stack is an abstract data type that serves as a collection of elements, with two main principal operations:
In computer science, computer engineering and programming language implementations, a stack machine is a type of computer. In some cases, the term refers to a software scheme that simulates a stack machine.
Addressing modes are an aspect of the instruction set architecture in most central processing unit (CPU) designs. The various addressing modes that are defined in a given instruction set architecture define how the machine language instructions in that architecture identify the operand(s) of each instruction. An addressing mode specifies how to calculate the effective memory address of an operand by using information held in registers and/or constants contained within a machine instruction or elsewhere.
In computer programming, a return statement causes execution to leave the current subroutine and resume at the point in the code immediately after the instruction which called the subroutine, known as its return address. The return address is saved by the calling routine, today usually on the process's call stack or in a register. Return statements in many languages allow a function to specify a return value to be passed back to the code that called the function.
In computer science, a tail call is a subroutine call performed as the final action of a procedure. If the target of a tail is the same subroutine, the subroutine is said to be tail-recursive, which is a special case of direct recursion. Tail recursion is particularly useful, and often easy to handle in implementations.
In computer science, a call stack is a stack data structure that stores information about the active subroutines of a computer program. This kind of stack is also known as an execution stack, program stack, control stack, run-time stack, or machine stack, and is often shortened to just "the stack". Although maintenance of the call stack is important for the proper functioning of most software, the details are normally hidden and automatic in high-level programming languages. Many computer instruction sets provide special instructions for manipulating stacks.
In computer science, a calling convention is an implementation-level (low-level) scheme for how subroutines receive parameters from their caller and how they return a result. Differences in various implementations include where parameters, return values, return addresses and scope links are placed, and how the tasks of preparing for a function call and restoring the environment afterward are divided between the caller and the callee.
Peephole optimization is an optimization technique performed on a small set of compiler-generated instructions; the small set is known as the peephole or window.
A stack register is a computer central processor register whose purpose is to keep track of a call stack. On an accumulator-based architecture machine, this may be a dedicated register such as SP on an Intel x86 machine. On a general register machine, it may be a register which is reserved by convention, such as on the PDP-11 or RISC machines. Some designs such as the Data General Eclipse had no dedicated register, but used a reserved hardware memory address for this function.
Control tables are tables that control the control flow or play a major part in program control. There are no rigid rules about the structure or content of a control table—its qualifying attribute is its ability to direct control flow in some way through "execution" by a processor or interpreter. The design of such tables is sometimes referred to as table-driven design. In some cases, control tables can be specific implementations of finite-state-machine-based automata-based programming. If there are several hierarchical levels of control table they may behave in a manner equivalent to UML state machines
The Perl virtual machine is a stack-based process virtual machine implemented as an opcodes interpreter which runs previously compiled programs written in the Perl language. The opcodes interpreter is a part of the Perl interpreter, which also contains a compiler in one executable file, commonly /usr/bin/perl on various Unix-like systems or perl.exe on Microsoft Windows systems.
In computer programming, a subroutine is a sequence of program instructions that performs a specific task, packaged as a unit. This unit can then be used in programs wherever that particular task should be performed.
The STM8 is an 8-bit microcontroller family by STMicroelectronics. The STM8 microcontrollers use an extended variant of the ST7 microcontroller architecture. STM8 microcontrollers are particularly low cost for a full-featured 8-bit microcontroller.