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作者 Hughes, Christopher J., author
書名 Single-instruction multiple-data execution / Christopher J. Hughes
出版項 San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2015
國際標準書號 9781627057646 e-book
9781627057639 print
國際標準號碼 10.2200/S00647ED1V01Y201505CAC032 doi
book jacket
說明 1 online resource (xv, 105 pages) : illustrations
text rdacontent
electronic isbdmedia
online resource rdacarrier
系列 Synthesis lectures on computer architecture, 1935-3243 ; # 32
Synthesis digital library of engineering and computer science
Synthesis lectures in computer architecture ; # 32. 1935-3243
附註 Part of: Synthesis digital library of engineering and computer science
Includes bibliographical references (pages 95-103)
1. Data parallelism -- 1.1 Data parallelism -- 1.2 Data parallelism in applications -- 1.2.1 Physical simulation -- 1.2.2 Computer vision -- 1.2.3 Speech recognition -- 1.2.4 Database management systems -- 1.2.5 Financial analytics -- 1.2.6 Medical imaging --
2. Exploiting data parallelism with SIMD execution -- 2.1 Exploiting data parallelism -- 2.2 SIMD execution -- 2.3 SIMD performance and energy benefits -- 2.4 Limits to SIMD scaling -- 2.5 Programming and compilation -- 2.5.1 Programming for SIMD execution -- 2.5.2 Challenges of static analysis --
3. Computation and control flow -- 3.1 SIMD registers -- 3.2 SIMD computation -- 3.2.1 Basic arithmetic and logic -- 3.2.2 Data element size and overflow -- 3.2.3 Advanced arithmetic -- 3.3 Control flow -- 3.3.1 SIMD execution with control flow -- 3.3.2 Conditional SIMD execution -- 3.3.3 Efficiency implications of control divergence --
4. Memory operations -- 4.1 Contiguous patterns -- 4.1.1 Unaligned accesses -- 4.1.2 Throughput implications -- 4.2 Non-contiguous patterns -- 4.2.1 Programming model issues -- 4.2.2 Implementing gather and scatter instructions -- 4.2.3 Locality in gathers and scatters --
5. Horizontal operations -- 5.1 Limits to horizontal operations -- 5.2 Data movement -- 5.3 Reductions -- 5.4 Reducing control divergence -- 5.5 Potential dependences -- 5.5.1 Single-index case -- 5.5.2 Multi-index case --
6. Conclusions -- 6.1 Future directions -- Bibliography -- Author's biography
Abstract freely available; full-text restricted to subscribers or individual document purchasers
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Having hit power limitations to even more aggressive out-of-order execution in processor cores, many architects in the past decade have turned to single-instruction-multiple-data (SIMD) execution to increase single-threaded performance. SIMD execution, or having a single instruction drive execution of an identical operation on multiple data items, was already well established as a technique to efficiently exploit data parallelism. Furthermore, support for it was already included in many commodity processors. However, in the past decade, SIMD execution has seen a dramatic increase in the set of applications using it, which has motivated big improvements in hardware support in mainstream microprocessors. The easiest way to provide a big performance boost to SIMD hardware is to make it wider. i.e., increase the number of data items hardware operates on simultaneously. Indeed, microprocessor vendors have done this. However, as we exploit more data parallelism in applications, certain challenges can negatively impact performance. In particular, conditional execution, noncontiguous memory accesses, and the presence of some dependences across data items are key roadblocks to achieving peak performance with SIMD execution. This book first describes data parallelism, and why it is so common in popular applications. We then describe SIMD execution, and explain where its performance and energy benefits come from compared to other techniques to exploit parallelism. Finally, we describe SIMD hardware support in current commodity microprocessors. This includes both expected design tradeoffs, as well as unexpected ones, as we work to overcome challenges encountered when trying to map real software to SIMD execution
Also available in print
Mode of access: World Wide Web
System requirements: Adobe Acrobat Reader
Title from PDF title page (viewed on June 20, 2015)
鏈接 Print version: 9781627057639
主題 SIMD (Computer architecture)
Parallel file systems (Computer science)
SIMD
vector processor
data parallelism
autovectorization
control divergence
vector masks
unaligned accesses
non-contiguous accesses
gather/scatter
horizontal operations
vector reductions
shuffle
permute
conflict detection
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