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dissipation costs are disproportionate. Moreover, the complexity and often the latency of the underlying hardware structures results in reduced operating frequency further reducing any benefits. Hence, the aforementioned techniques prove inadequate to keep the CPU from stalling for the off-chip data. Instead, the industry is heading towards exploiting higher levels of parallelism that can be exploited through techniques such as
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which allows the execution of complete instructions or parts of instructions before being certain whether this execution should take place. A commonly used form of speculative execution is control flow speculation where instructions past a control flow instruction (e.g., a branch) are executed before
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Operation 3 depends on the results of operations 1 and 2, so it cannot be calculated until both of them are completed. However, operations 1 and 2 do not depend on any other operation, so they can be calculated simultaneously. If we assume that each operation can be completed in one unit of time
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used ILP techniques to overcome the limitations imposed by a relatively small register file). Presently, a cache miss penalty to main memory costs several hundreds of CPU cycles. While in principle it is possible to use ILP to tolerate even such memory latencies, the associated resource and power
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designers is to identify and take advantage of as much ILP as possible. Ordinary programs are typically written under a sequential execution model where instructions execute one after the other and in the order specified by the programmer. ILP allows the compiler and the processor to overlap the
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It is known that the ILP is exploited by both the compiler and hardware support but the compiler also provides inherent and implicit ILP in programs to hardware by compile-time optimizations. Some optimization techniques for extracting available ILP in programs would include
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Hardware level works upon dynamic parallelism, whereas the software level works on static parallelism. Dynamic parallelism means the processor decides at run time which instructions to execute in parallel, whereas static parallelism means the
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where instructions execute in any order that does not violate data dependencies. Note that this technique is independent of both pipelining and superscalar execution. Current implementations of out-of-order execution
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In recent years, ILP techniques have been used to provide performance improvements in spite of the growing disparity between processor operating frequencies and memory access times (early ILP designs such as the
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which refers to a technique used to avoid unnecessary serialization of program operations imposed by the reuse of registers by those operations, used to enable out-of-order execution.
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the target of the control flow instruction is determined. Several other forms of speculative execution have been proposed and are in use including speculative execution driven by
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176:(i.e., while the program is executing and without any help from the compiler) extract ILP from ordinary programs. An alternative is to extract this parallelism at
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and somehow convey this information to the hardware. Due to the complexity of scaling the out-of-order execution technique, the industry has re-examined
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which is used to avoid stalling for control dependencies to be resolved. Branch prediction is used with speculative execution.
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51:. More specifically ILP refers to the average number of instructions run per step of this parallel execution.
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How much ILP exists in programs is very application specific. In certain fields, such as graphics and
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then these three instructions can be completed in a total of two units of time, giving an ILP of 3/2.
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are another class of architectures where ILP is explicitly specified, for a recent example see the
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execution of multiple instructions or even to change the order in which instructions are executed.
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Ability of computer instructions to be executed simultaneously with correct results
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Aiken, Alex; Banerjee, Utpal; Kejariwal, Arun; Nicolau, Alexandru (2016-11-30).
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Goossens, Bernard; Langlois, Philippe; Parello, David; Petit, Eric (2012).
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where the execution of multiple instructions can be partially overlapped.
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https://www.scribd.com/doc/33700101/Instruction-Level-Parallelism#scribd
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which explicitly encode multiple independent operations per instruction.
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322:. Lecture Notes in Computer Science. Vol. 7133. pp. 270–281.
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processor works on the dynamic sequence of parallel execution, but the
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Micro-architectural techniques that are used to exploit ILP include:
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There are two approaches to instruction-level parallelism:
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the amount can be very large. However, workloads such as
316:"PerPI: A Tool to Measure Instruction Level Parallelism"
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decides which instructions to execute in parallel. The
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are used to execute multiple instructions in parallel.
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Wired magazine article that refers to the above paper
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http://www.hpl.hp.com/techreports/92/HPL-92-132.pdf
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397:. Professional Computing (1 ed.). Springer.
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102:processor works on the static level parallelism.
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359:Hennessy, John L.; Patterson, David A. (1996).
363:Computer Architecture: A Quantitative Approach
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28:, the first computer with parallel processing
228:/renaming, and memory access optimization.
2244:Computer performance by orders of magnitude
43:or simultaneous execution of a sequence of
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320:Applied Parallel and Scientific Computing
159:explicitly parallel instruction computing
428:Approaches to addressing the Memory Wall
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2215:Floating-point operations per second
63:. In ILP there is a single specific
137:may exhibit much less parallelism.
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105:Consider the following program:
3116:History of general-purpose CPUs
1343:Nondeterministic Turing machine
678:Analysis of parallel algorithms
1296:Deterministic finite automaton
378:Reflections of the Memory Wall
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109:e = a + b f = c + d m = e * f
59:ILP must not be confused with
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2087:Simultaneous and heterogenous
625:Simultaneous and heterogenous
395:Instruction Level Parallelism
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33:Instruction-level parallelism
2771:Integrated memory controller
2753:Translation lookaside buffer
1952:Memory dependence prediction
1395:Random-access stored program
1348:Probabilistic Turing machine
1213:Category: Parallel computing
328:10.1007/978-3-642-28151-8_27
203:memory dependence prediction
161:concepts, in which multiple
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2227:Synaptic updates per second
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2631:Heterogeneous architecture
1553:Orthogonal instruction set
1323:Alternating Turing machine
1311:Quantum cellular automaton
520:High-performance computing
291:"The History of Computing"
157:, and the closely related
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2479:Digital signal processor
2456:Graphics processing unit
2268:Graphics processing unit
270:Memory-level parallelism
207:cache latency prediction
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26:Atanasoff–Berry computer
3089:Dynamic voltage scaling
2872:Memory address register
2766:Branch target predictor
2730:Address generation unit
2473:Physics processing unit
2262:Central processing unit
2221:Transactions per second
2209:Instructions per second
2132:Array processing (SIMT)
1276:Stored-program computer
1169:Embarrassingly parallel
1164:Deterministic algorithm
244:IBM System/360 Model 91
3177:Instruction processing
2895:Hardwired control unit
2777:Memory management unit
2742:Memory management unit
2491:Secure cryptoprocessor
2485:Tensor Processing Unit
2467:Vision processing unit
2201:Cycles per instruction
2195:Instructions per cycle
2142:Associative processing
1833:Instruction pipelining
1255:Processor technologies
884:Associative processing
840:Non-blocking algorithm
646:Clustered multi-thread
232:Dataflow architectures
222:instruction scheduling
169:Out-of-order execution
145:Instruction pipelining
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2978:Sum-addressed decoder
2724:Arithmetic logic unit
1851:Classic RISC pipeline
1805:Epiphany architecture
1652:Motorola 68000 series
1000:Hardware acceleration
913:Superscalar processor
903:Dataflow architecture
500:Distributed computing
194:Speculative execution
24:
3099:Performance per watt
2677:replacement policies
2343:Package on a package
2233:Performance per watt
2137:Pipelined processing
1907:Tomasulo's algorithm
1712:Clipper architecture
1568:Application-specific
1281:Finite-state machine
879:Pipelined processing
828:Explicit parallelism
823:Implicit parallelism
813:Dataflow programming
131:scientific computing
3131:Digital electronics
2784:Instruction decoder
2736:Floating-point unit
2390:Soft microprocessor
2337:System in a package
1912:Reservation station
1442:Transport-triggered
1103:Parallel Extensions
908:Pipelined processor
226:register allocation
3182:Parallel computing
3003:Integrated circuit
2847:Processor register
2501:Baseband processor
1846:Operand forwarding
1306:Cellular automaton
977:Massively parallel
955:distributed shared
775:Cache invalidation
739:Instruction window
530:Manycore processor
510:Massively parallel
505:Parallel computing
486:Parallel computing
448:2016-03-04 at the
236:TRIPS architecture
67:of execution of a
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2672:Instruction cache
2662:Scratchpad memory
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2331:Multi-chip module
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1617:VISC architecture
1499:Secondary storage
1415:Microarchitecture
1375:Register machines
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1174:Parallel slowdown
808:Stream processing
698:Karp–Flatt metric
404:978-1-4899-7795-3
337:978-3-642-28150-1
213:Branch prediction
188:Register renaming
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3018:Power management
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1271:Abstract machine
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770:Cache coherence
760:Multiprocessing
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3156:Chip carrier
3094:Clock gating
3013:Mixed-signal
2910:Write buffer
2887:Control unit
2699:Clock signal
2438:accelerators
2420:Cypress PSoC
2077:Simultaneous
1997:
1894:Out-of-order
1526:Neuromorphic
1407:Architecture
1365:Belt machine
1358:Zeno machine
1291:Hierarchical
753:Coordination
683:Amdahl's law
619:Simultaneous
565:
394:
373:
362:
354:
319:
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298:. Retrieved
294:
285:
240:
230:
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178:compile time
139:
135:cryptography
128:
116:
112:
104:
88:
77:
58:
45:instructions
36:
32:
31:
18:
2941:Multiplexer
2905:Data buffer
2616:Single-core
2588:bit slicing
2446:Coprocessor
2301:Coprocessor
2182:performance
2104:Cooperative
2094:Speculative
2054:Distributed
2013:Superscalar
1998:Instruction
1966:Parallelism
1939:Speculative
1771:System/3x0
1643:Instruction
1420:Von Neumann
1333:Post–Turing
1189:Scalability
950:distributed
833:Concurrency
800:Programming
641:Cooperative
630:Speculative
566:Instruction
417:(276 pages)
174:dynamically
153:execution,
151:Superscalar
61:concurrency
3171:Categories
3061:management
2956:Multiplier
2817:Logic gate
2807:Sequential
2714:Functional
2694:Clock rate
2667:Data cache
2640:Components
2621:Multi-core
2609:Core count
2099:Preemptive
2003:Pipelining
1986:Bit-serial
1929:Wide-issue
1874:Structural
1796:Tilera ISA
1762:MicroBlaze
1732:ETRAX CRIS
1627:Comparison
1472:Load–store
1452:Endianness
1194:Starvation
933:asymmetric
668:PRAM model
636:Preemptive
300:2019-03-24
277:References
117:A goal of
55:Discussion
2995:Circuitry
2915:Microcode
2839:Registers
2682:coherence
2657:CPU cache
2515:Word size
2180:Processor
1824:Execution
1727:DEC Alpha
1705:Power ISA
1521:Cognitive
1328:Universal
928:symmetric
673:PEM model
123:processor
39:) is the
2933:Datapath
2626:Manycore
2598:variable
2436:Hardware
2072:Temporal
1752:OpenRISC
1447:Cellular
1437:Dataflow
1430:modified
1159:Deadlock
1147:Problems
1113:pthreads
1093:OpenHMPP
1018:Ateji PX
979:computer
850:Hardware
717:Elements
703:Slowdown
614:Temporal
596:Pipeline
446:Archived
346:26665479
259:See also
119:compiler
92:compiler
84:software
80:hardware
41:parallel
3109:Related
3040:Quantum
3030:Digital
3025:Boolean
2923:Counter
2822:Quantum
2583:512-bit
2578:256-bit
2573:128-bit
2416:(MPSoC)
2401:on chip
2399:Systems
2217:(FLOPS)
2030:Process
1879:Control
1861:Hazards
1747:Itanium
1742:Unicore
1700:PowerPC
1425:Harvard
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1118:RaftLib
1098:OpenACC
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1038:Charm++
780:Barrier
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493:General
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3045:Switch
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2773:(IMC)
2744:(MMU)
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2229:(SUPS)
2197:(IPC)
2049:Memory
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2008:Scalar
1810:Others
1757:RISC-V
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1691:Power
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401:
344:
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2203:(CPI)
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970:COMA
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896:MIMD
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2918:ROM
2689:Bus
2306:PAL
1981:Bit
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1672:ARM
1667:x86
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1138:ZPL
1133:TBB
1128:UPC
1108:PVM
1078:MPI
1033:HPX
960:UMA
561:Bit
324:doi
86:.
73:CPU
37:ILP
3173::
3008:3D
407:.
340:.
330:.
318:.
293:.
255:.
238:.
224:,
201:,
1247:e
1240:t
1233:v
478:e
471:t
464:v
415:.
367:.
348:.
326::
303:.
209:.
35:(
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