A virtual machine, sense 1, is an abstraction that defines a ComputingModel?
. Also called an AbstractMachine
A virtual machine, sense 2, is also an implementation, done over another virtual machine, sense 2, or directly into hardware, of a virtual machine, sense 1.
In recent years the term has come to have the connotation of a software platform that exists on multiple hardware platforms and provides an abstraction layer that allows programmers to write code without considering the hardware that it will run on.
Examples throughout the history of our field:
For general-purpose ProgrammingLanguage
Special purpose machines:
Interesting subtype of VirtualMachine
- SafeVirtualMachine (guarantees, that code cannot violate its typing, thus enforcing security):
considered an example of VirtualMachine
I just added VirtualComputer to try to clarify the distinction, at least on this Wiki.
: fancy name for computer program, see also: TuringMachine
is a program that translates a standard series of instruction codes into hardware specific MachineLanguage
. In recent years the term has come to have the connotation of a software platform that exists on multiple hardware platforms and provides an abstraction layer that allows programmers to write code without considering the hardware that it will run on.
That sounds more like a definition of a compiler/assembler than a VirtualMachine. Particularly in the context of an interpreter (or microcode), MachineLanguage instructions, while executed to perform the higher level functions, are not necessarily first emitted as the result of some translation process. And I'm not sure about calling a VirtualMachine a program, instead it is the non-tangible specification of a device, which can be used only through an emulation program.
Any interpreted language and most operating systems operate as virtual machines but the term has gained prominence in part due to the popularity of the JavaLanguage
The term has gained prominence in the past, due to Pcode and ByteCodes?
What about the following definition:
A virtual machine is a hypothetical device that is capable of executing a
specific instruction set. Such an instruction set is commonly called ByteCode
A common implementation strategy for programming
languages is to compile code into instructions for a specialized VirtualMachine
Subsequently, these instructions can be actually executed in a number of different ways:
- Interpretation by software
- Translation into the instruction set of a real processor
- Direct interpretation in hardware
In the last case, the virtual machine isn't "virtual" anymore, though the name
may still stick if there's a long history during which the machine was really
Confusingly, the software interpreter for a virtual machine is itself also
sometimes called a virtual machine. It is more correctly called a ByteCodeInterpreter?
An implementation strategy which compiles ByteCode
into the instruction set of the real processor just prior to execution, is called JustInTimeCompilation
Not all virtual machines are interpreters, not all virtual machines use a stack-based paradigm, and not all software interpreters (sic) for virtual machines are ByteCodeInterpreter?
s. I suggest that we therefore broaden the definition of virtual machine.
, we built a virtual machine that ran compiled code in a virtual machine that used a RISC-based register-intensive paradigm. The virtual machine was therefore a generic RISC engine for which we defined intermediate code (like that of a portable compiler). Compilers (we supported Smalltalk and ObjectiveCee
) emitted intermediate code for each method, which was then persisted (instead of ByteCode
s). Native code was compiled by a platform-specific code generator as each method was imported into the environment or compiled after being edited.
Thus, the ComponentVirtualMachine?
always ran compiled code, it only required JustInTimeCompilation
for performs and similar exotica, and its performance was dramatically better than comparable byte-code approaches. The code generator for RISC machines (our prototype ran on MacII's and Sparc's) could generate blazing native code.
I would like to point out that a virtual machine can
be done in such a way to run fast, the JavaVirtualMachine
is not a very good example.
For example, being stack based is very nice in theory. It is a clean design and computer scientists love clean designs. But they are
a bad idea. See this example of translating "a = b + c":
push b LS
push c LS
pop a LS
Compare with a more flexible approach, where operators can use memory directly for example:
add b, c, a LLS
Pushes and pops have to store/load, because most of the time they are implemented with a piece of regular memory. This makes the stack-based example do 5 loads and 4 stores, spanning 4 instructions (think instruction decoding overhead). A saner (and not as clean, design-wise) way to do this is to have an 'add' operator that will add two memory locations and put the result in a third memory location. A single instruction, two loads, one store.
This may be true for stack architectures made by register-familiar engineers, but true stack architectures (e.g., actual hardware that runs stack-oriented code, a la Forth CPUs) are actually notably faster than register-oriented architectures, by virtue of the fact that the interconnects to/from the ALU are fixed and substantially shorter, going through fewer gates, and therefore, can be driven at substantially higher clock rates (Chuck Moore's MuP21 achieved 500MIPS peak performance with 0.8u technology, for example). Of course, that being said, implementing a stack virtual machine on a register architecture will slow things down considerably, just as implementing a register-based VM on a stack architecture will bog it down considerably.
Also, stack architectures with small, finite stack depths are able to be 'register-optimized' with moderate ease. For example, anyone here can probably write an optimizing virtual machine implementation for the Steamer16 microprocessor that runs close to, if not at, native hardware speed on a register-based architecture.
- The stack example can be rewritten using modern compiler techniques and simplified to your 3-operand example. StaticSingleAssignmentForm is your friend! I believe this is what most native-code JavaLanguage compilers do, and with quite admirable results. This allows a restoration of using the clean design of the stack, while factoring out the brutal realities of register-based architectures. --SamuelFalvo?
Do this with other instructions (complicate
them) and try it. Speed! Still less than native code, of course, but getting better. And those "complex instructions" have more context to them, so that a JustInTimeCompiler
could possibly have more success optimizing them. For example, a very complex instruction (think really stupidly complex, like a 'sort' operator!) could be compiled to a function call into some hand-optimized C or assembler code, as tight as you could want. This would be much faster than implementing it in the virtual machine.
For an example of such a VirtualMachine
, look at http://www.cs.bell-labs.com/cm/cs/who/rob/hotchips.html
, by RobPike
Actually, this is very common (Sun just seems to miss all of these things). If you look at IBM's BAL for the 360/370/390 lineage or MI for the AS/400 [AsFourHundredMachineInterface?] you will see this kind of an approach. IBM has always used an "abstract" assembler, which is to say that you aren't programming the processor in a direct fashion. On the AS/400 all program objects run in a virtual machine environment. On the mainframe this is less the case, but still close. Many of the opcodes are optimized for minimum load/stores. Also, you will tend to find "higher level" opcodes than in say pure RISC or other CISC assemblers.
It's still not good enough for a portable
virtual machine (not necessarily the goal of the IBM/3?0 group). See http://sunir.org/apps/vm?RedCode
for a discussion of this.
I wonder if the best form for a VM instruction set might not be some sort of StaticSingleAssignmentForm
. SSA is elegant enough to satisfy the ComputerScience
propellerheads, and is easy to compile into good code - SSA is used as an intermediate form in many (most?) modern compilers. The only serious problem i can think of is running it by interpretation or fast compilation (where proper register allocation is too expensive); this might be ameliorated by doing some sort of register allocation at source-compile-time, and including the results as a hint to the interpreter. -- TomAnderson
(LLVM) uses this, I believe. -- JebadiahMoore?
I think compressed AbstractSyntaxTree
s might be better. I found a reference (although I'm not going to look right now) that showed that due to the growing latency gap between processors and disks, loading compressed abstract syntax trees off disk and compiling them on the fly was faster than loading
a purely native program off disk.
There was also another operating system
?) that stored all the programs and system libraries as ASTs and recompiled each function on the fly as it was invoked. They saw something like a magnitude speed improvement over purely native call (think dynamic
Then again, http://www.bytecodes.com
claims their embedded JVM is comparable to embedded JVMs with JIT compilers because they can stuff the VM runtime into the instruction cache and most programs into the data cache. JIT compilers would thrash both caches very badly. -- SunirShah
True, but they also say "Large desktop and server platforms with megabytes of memory to spare and processors running over 2 Gigahertz with 256K on-chip caches are better served by using the fully optimizing versions of server and desktop Just-In-Time Compilers (JITs) coupled with our EBCI Interpreters. JITs use our interpreters to jump start at a faster speed because JITs start out interpreting Java code before compiling it."
TAOS (now TaoIntentOs
) was designed to operate on heterogenous clusters (eg a mix of PC and sparc hardware on an ethernet), so it defined programs in terms of a virtual processor (and so an associated VirtualMachine
); it was translated into native code at load time. They say: "It would be wrong to think that this slows the system down. Most processors are able to translate VP into native code faster than the VP code can be loaded from disk and sent across the network, so there is no visible overhead. Indeed, VP code is often more compact than the native code; therefore less disk space is used and code is loaded faster than if it were the native for the processor."
Parrot has a register-based design for its JIT VM.
One of the world's earliest and most widely ported virtual machines is the z-code interpreter from Infocom.
In various incarnations it was used to implement the 35 or so text adventure games they released allowing
their games, including the famous Zork Trilogy, to be platform independent. Z-code interpreters exist for platforms as diverse as the Commodore64, AppleII,
PalmOS, KayproII, IBMPC, TRS-80 and the TI-89 calculator. A compiler for this virtual machine, Inform, is freely available
although the original games were not written with this compiler.
UCSD Pascal was earlier and more widely ported, note. Mainframe emulators were widely used back in the 1960s to maintain backward compatibility. Z-code might hold a record for the product of EARLIEST * WIDELY_PORTED; back then it was unusual for anything at all to be widely ported.
There are probably more people served by PickLanguage
s and HumanRelationsSystem?
s, even now in 2006. On a VirtualMachine
within many corporate operating systems, including Windows, Unix, MVS.
See also: GlobalVariablesAndVirtualMachines
(because of the close associations)