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But typical basic blocks are small. – 3-6 instruction (15%-25% branch frequency). 0. Optimizing across branches is a must. – Examples: loop-level parallelism, data parallelism (SIMD). 4. Instruction Parallelism Examples. 0. Loop-level parallelism. – Loop unrolling (compiler). – Dynamic unrolling (superscalar scheduling).
Instruction-level parallelism (ILP) is a measure of how many of the instructions in a computer program can be executed simultaneously. There are two approaches to instruction level parallelism: Hardware.
23 Feb 2015
Scheduling. • Central problem to ILP processing. – need to determine when parallelism (independent instructions) exists. – in Pentium example, decode stage checks for multiple conditions: •is there a data dependency? – does one instruction generate a value needed by the other? – do both instructions write to the same
What is instruction-level parallelism? • What do processors do to extract at the same time. • A perfect machine with infinite machine parallelism can achieve the ILP of a program. •To achieve high performance, need both ILP and machine parallelism . In-Order Issue, In-Order Completion Example. EX. IF. ID. WB. I n s t r. O.
200 items Motivating Example. The goal with pipelining is to speed things up. More specifically, we want to increase the throughput of the system, where throughput is . In the simple pipeline we have seen, ILP can be hard to come by; however, there are many tricks people have invented for squeezing more ILP out of the
Data Level Parallelsim Data level parallelism (DLP) is more of a special case than instruction level parallelism. DLP to the act of performing the same operation on multiple datum simultaneously. A classic example of DLP is performing an operation on an image in which processing each pixel is independent from the ones
13 Apr 2015 Hierarchy Bit level Parallelism • 16 bit add on 8 bit processor Instruction level Parallelism Loop level Parallelism • for (i=1; i<=1000; i= i+1) x[i] = x[i] + y[i]; Thread level Parallelism • multi-core computers; 4. EXAMPLE Consider the following program: 1. e = a + b 2. f = c + d 3. g = e * f Operation 3
In contrast to: • loop-level parallelism (medium-grained). • process-level or task-level or thread-level parallelism (coarse- grained). Instruction-Level Parallelism (ILP). Can be exploited when instruction operands are independent of each other, for example,. • two instructions are independent if their operands are different.
The simplest and most common way to increase the amount of parallelism available among instructions is to exploit parallelism among iterations of a loop. This type of parallelism is often called loop-level parallelism. Example 1. for (i=1; i<=1000; i= i+1) x[i] = x[i] + y[i];. This is a parallel loop. Every iteration of the loop can
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