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1. Top results related to what is instruction-level parallelism (ilp)?

   • Is there a really working example which showing the benefits of ILP(Instruction-Level Parallelism) on x86_64?

     Top Answer

     Answered Jan 02, 2015 · 15 votes

     On most Intel processors, it takes 3 cycles to do a floating-point add. But it can sustain up to 1/cycle if they are independent.

     We can easily demonstrate ILP by putting a floating-point add on the critical path.

     Environment:

     • GCC 4.8.2: -O2
     • Sandy Bridge Xeon

     Make sure that the compiler does not do unsafe floating-point optimizations.

     #include <iostream>using namespace std;-#include <time.h>-const int iterations = 1000000000;-double sequential(){ double a = 2.3; double result = 0;- for (int c = 0; c < iterations; c += 4){ // Every add depends on the previous add. No ILP is possible. result += a; result += a; result += a; result += a; }- return result;}double optimized(){ double a = 2.3; double result0 = 0; double result1 = 0; double result2 = 0; double result3 = 0;- for (int c = 0; c < iterations; c += 4){ // 4 independent adds. Up to 4 adds can be run in parallel. result0 += a; result1 += a; result2 += a; result3 += a; }- return result0 + result1 + result2 + result3;}-int main(){- clock_t start0 = clock(); double sum0 = sequential(); clock_t end0 = clock(); cout << "sum = " << sum0 << endl; cout << "sequential time: " << (double)(end0 - start0) / CLOCKS_PER_SEC << endl;- clock_t start1 = clock(); double sum1 = optimized(); clock_t end1 = clock(); cout << "sum = " << sum1 << endl; cout << "optimized time: " << (double)(end1 - start1) / CLOCKS_PER_SEC << endl;-}-

     Output:

     sum = 2.3e+09sequential time: 0.948138sum = 2.3e+09optimized time: 0.317293-

     Notice how the difference is almost exactly 3x. That's because of the 3-cycle latency and 1-cycle throughput of the floating-point add.

     The sequential version has very little ILP because all the floating-point adds are on the critical path. (each add needs to wait until the previous add is done) The unrolled version has 4 separate dependency chains with up to 4 independent adds - all of which can be run in parallel. Only 3 are required to saturate the processor core.

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   • Instruction Level Parallelism

     Instruction Level Parallelism (ILP) is used to refer to the architecture in which multiple operations can be performed parallelly in a particular process, with its own set of resources – address space, registers, identifiers, state, and program counters. It refers to the compiler design techniques and processors designed to execute operations, like memory load and store, integer addition, and float multiplication, in parallel to improve the performance of the processors.

     Examples of architectures that exploit ILP are VLIWs and superscalar Architecture. ILP processors have the same execution hardware as RISC processors. The machines without ILP have complex hardware which is hard to implement. A typical ILP allows multiple-cycle operations to be pipelined.

     Example: Suppose, 4 operations can be carried out in a single clock cycle. So there will be 4 functional units, each attached to one of the operations, branch unit, and common register file in the ILP execution hardware. The sub-operations that can be performed by the functional units are Integer ALU, Integer Multiplication, Floating Point Operations, Load, and Store. Let the respective latencies be 1, 2, 3, 2, 1.

     Let the sequence of instructions by...

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     2/5

   • Instruction Level Parallelism

     Instruction Level Parallelism (ILP) is used to refer to the architecture in which multiple operations can be performed parallelly in a particular process, with its own set of resources – address space, registers, identifiers, state, and program counters. It refers to the compiler design techniques and processors designed to execute operations, like memory load and store, integer addition, and float multiplication, in parallel to improve the performance of the processors.

     Examples of architectures that exploit ILP are VLIWs and superscalar Architecture. ILP processors have the same execution hardware as RISC processors. The machines without ILP have complex hardware which is hard to implement. A typical ILP allows multiple-cycle operations to be pipelined.

     Example: Suppose, 4 operations can be carried out in a single clock cycle. So there will be 4 functional units, each attached to one of the operations, branch unit, and common register file in the ILP execution hardware. The sub-operations that can be performed by the functional units are Integer ALU, Integer Multiplication, Floating Point Operations, Load, and Store. Let the respective latencies be 1, 2, 3, 2, 1.

     Let the sequence of instructions by...

     Check all answers on Geeksforgeeks

     3/5

   • Instruction level parallelism vs SIMD

     Top Answer

     Answered May 23, 2017 · 2 votes

     SIMD is having each instruction process multiple items. ILP is about having multiple dependency chains so multiple instructions can be in flight at once.

     They are orthogonal; to max out Haswell's FMA throughput, you need to keep 10 FMAs in flight, each one operating on a vector of 8 single-precision elements.

     The x86 tag wiki has lots of links, especially Agner Fog's Optimizing Assembly and microarchitecture guides to understand more about throughput vs. latency.

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     4/5

   • Is having multiple cores in a CPU for running multiple threads/processes at once, or for instruction-level parallelism?

     Top Answer

     Answered May 10, 2021 · 3 votes

     ILP is purely within each physical core separately. cross-site duplicate: How does a single thread run on multiple cores? (It doesn't - each core has multiple execution units and a wide front-end. Read my linked answer for details that I'm not going to duplicate. See also Modern Microprocessors A 90-Minute Guide!)

     Also, real CPU cores can pretend to be multiple "logical cores" (i.e. each having register context and can call __schedule() independently). Generically, this is SMT; the mostly widely-known brand-name implementation of that concept is Intel's HyperThreading. Letting multiple software threads share a CPU truly simultaneously (not via software context-switching) gives the core two instruction-streams to find parallelism between as well as within, generally increasing overall throughput (at the cost of single-thread performance to some degree, depending on how busy a single thread of your workload could keep a core).

     In some contexts, "CPU" is synonym for a single core. e.g. perf stat output saying "7.5 CPUs utilized".

     But more often, a CPU refers to the whole physical package, e.g. my CPU is a quad-core, an i7-6700k. Server motherboards are often dual-socket, allowing you to plug in two separate multi-core CPUs.

     Perhaps that's what created some terminology confusion?

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     5/5

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2. People also ask

   What is instruction-level parallelism (ILP)?

   • Instruction-level parallelism ( ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically ILP refers to the average number of instructions run per step of this parallel execution. : 5 ILP must not be confused with concurrency.

   Instruction-level parallelism - Wikipedia

   en.wikipedia.org/wiki/Instruction-level_parallelism

   See all results for this question

   What is loop-level parallelism?

   • loop-level parallelism (medium-grained) process-level or task-level or thread-level parallelism (coarse-grained) two instructions are independent if their operands are different an example of independent instructions consumer instruction gets a value from a producer instruction determines the order in which instructions can be executed

   Instruction-Level Parallelism (ILP) - University of Washington

   courses.cs.washington.edu/courses/cse471/09sp/lectures/pipeliningBasics.pdf

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   What is ILP and how does it work?

   • ILP allows the compiler and the processor to overlap the execution of multiple instructions or even to change the order in which instructions are executed. How much ILP exists in programs is very application specific. In certain fields, such as graphics and scientific computing the amount can be very large.

   Instruction-level parallelism - Wikipedia

   en.wikipedia.org/wiki/Instruction-level_parallelism

   See all results for this question

   What is overlap in ILP?

   • overlaps execution of different instructions execute all steps in the execution cycle simultaneously, but on different instructions Exploits ILP by executing several instructions “in parallel” Goal is to increase instruction throughput Not that simple! pipeline hazards (structural, data, control) place a “soft limit” on the number of stages

   Instruction-Level Parallelism (ILP) - University of Washington

   courses.cs.washington.edu/courses/cse471/09sp/lectures/pipeliningBasics.pdf

   See all results for this question

3. www.geeksforgeeks.org › instruction-level-parallelismInstruction Level Parallelism - GeeksforGeeks

   www.geeksforgeeks.org › instruction-level-parallelism

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   Sep 20, 2023 · Instruction Level Parallelism (ILP) is used to refer to the architecture in which multiple operations can be performed parallelly in a particular process, with its own set of resources – address space, registers, identifiers, state, and program counters.

4. en.wikipedia.org › wiki › Instruction-level_parallelismInstruction-level parallelism - Wikipedia

   en.wikipedia.org › wiki › Instruction-level_parallelism

   • Cached

   Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically ILP refers to the average number of instructions run per step of this parallel execution.

5. www.prepbytes.com › blog › computer-architectureInstruction level parallelism(ILP)

   www.prepbytes.com › blog › computer-architecture

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   Aug 8, 2023 · What is Instruction Level Parallelism (ILP)? ILP refers to the capability of a processor to execute multiple instructions simultaneously, taking advantage of independent instructions and reducing dependencies between them. In essence, ILP aims to identify and exploit parallelism within a sequential stream of instructions, thereby speeding up ...

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7. people.cs.pitt.edu › ~cho › cs2410What is instruction level parallelism? - University of Pittsburgh

   people.cs.pitt.edu › ~cho › cs2410

   Instruction Level Parallelism. Sangyeun Cho. Computer Science Department University of Pittsburgh. What is instruction level parallelism? Execute independent instructions in parallel. Provide more hardware function units (e.g., adders, cache ports) Detect instructions that can be executed in parallel (in hardware or software)

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8. courses.cs.washington.edu › courses › cse471Instruction-Level Parallelism (ILP) - University of Washington

   courses.cs.washington.edu › courses › cse471

   Instruction-Level Parallelism (ILP) Fine-grained parallelism Obtained by: • instruction overlap in a pipeline • executing instructions in parallel (later, with multiple instruction issue) In contrast to: • loop-level parallelism (medium-grained) • process-level or task-level or thread-level parallelism (coarse-grained)

9. learn.saylor.org › mod › pageCS301: Instruction-Level Parallelism | Saylor Academy

   learn.saylor.org › mod › page

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   Jul 28, 2020 · Parallelism can occur at different levels of granularity, and when discussing parallelism, we need to be clear on exactly what is being done in parallel. Instruction-level parallelism ( ILP ) is a measure of how many of the instructions in a computer program can be executed simultaneously.

10. www.nvidia.com › courses › ucdavisLecture 3 Instruction Level Parallelism (1) - NVIDIA

    www.nvidia.com › courses › ucdavis

    What is instruction-level parallelism? What do processors do to extract ILP? Not “how do they do that” (future lecture) . Why Do Processors Get Faster? 3 reasons: More parallelism (or more work per pipeline stage): fewer clocks/instruction [more instructions/cycle] Get WIDER. Deeper pipelines: fewer gates/clock. Get DEEPER.