Multicore Scaling: The ECM Model

Transcription

1 Multicore Scaling: The ECM Model Single-core performance prediction The saturation point Stencil code examples: 2D Jacobi in L1 and L2 cache 3D Jacobi in memory 3D long-range stencil G. Hager, J. Treibig, J. Habich, and G. Wellein: Exploring performance and power properties of modern multicore chips via simple machine models. Concurrency and Computation: Practice and Experience, DOI: /cpe.3180 (2013). Preprint: arxiv:

2 Assumptions and shortcomings of the roofline model Assumes one of two bottlenecks 1. In-core execution 2. Bandwidth of a single hierarchy level Latency effects are not modeled pure data streaming assumed In-core execution is sometimes hard to A(:)=B(:)+C(:)*D(:) model Saturation effects in multicore chips are not explained ECM model gives more insight Roofline predicts full socket BW 2

3 The Execution-Cache-Memory (ECM) model

4 ECM Model ECM = Execution-Cache-Memory Assumptions: Single-core execution time is composed of 1. In-core execution 2. Data transfers in the memory hierarchy Data transfers may or may not overlap with each other or with in-core execution Scaling is linear until the relevant bottleneck is reached Input: Same as for Roofline + data transfer times in hierarchy 4

5 Example: Schönauer Vector Triad in L2 cache REPEAT[ A(:) = B(:) + C(:) * double precision Analysis for Sandy Bridge core w/ AVX (unit of work: 1 cache line) Machine characteristics: Registers L1 1 LD/cy ST/cy Triad analysis (per CL): Registers L1 6 cy/cl Timeline: ADD ADD MULT MULT LD LD ST/2 LD ST/2 LD LD ST/2 16 F/CL (AVX) LD ST/2 32 B/cy (2 cy/cl) 10 cy/cl LD LD LD WA ST L2 L2 Roofline prediction: 16/10 F/cy Arithmetic: 1 ADD/cy+ 1 MULT/cy Arithmetic: AVX: 2 cy/cl Measurement: 16F / 17cy 5

6 Example: ECM model for Schönauer Vector Triad A(:)=B(:)+C(:)*D(:) on a Sandy Bridge Core with AVX CL transfer Writeallocate CL transfer 6

7 Multicore scaling in the ECM model Identify relevant bandwidth bottlenecks L3 cache Memory interface Scale single-thread performance until first bottleneck is hit: t threads: P t = min(tp 0, I b S ) Example: Scalable L3 on Sandy Bridge... 8

8 ECM prediction vs. measurements for A(:)=B(:)+C(:)*D(:) on a Sandy Bridge socket (no-overlap assumption) Model: Scales until saturation sets in Saturation point (# cores) well predicted Measurement: scaling not perfect Caveat: This is specific for this architecture and this benchmark! Check: Use overlappable kernel code 9

9 ECM prediction vs. measurements for A(:)=B(:)+C(:)/D(:) on a Sandy Bridge socket (full overlap assumption) In-core execution is dominated by divide operation (44 cycles with AVX, 22 scalar) Almost perfect agreement with ECM model General observation: If the L1 cache is 100% occupied by LD/ST, there is no overlap throughout the hierarchy If there is slack at the L1, there is overlap in the hierarchy 10

10 Performance Modeling of Stencil Codes Applying the ECM model to stencil updates: - 2D Jacobi smoother (DP, SSE) - 3D Jacobi smoother (DP, AVX) - Long-range stencil (SP, AVX) (H. Stengel, RRZE)

11 Example 1: 2D Jacobi in DP with SSE2 on Sandy Bridge 12

12 Example 1: 2D Jacobi in DP with SSE2 on SNB 4-way unrolling 8 LUP / iteration Instruction count - 13 LOAD - 4 STORE - 12 ADD - 4 MUL 13

13 Example 1: 2D Jacobi in DP with SSE2 on SNB Processor characteristics (SSE instructions per cycle) - 2 LOAD (1 LOAD + 1 STORE) - 1 ADD - 1 MUL Code characteristics (SSE instructions per iteration) - 13 LOAD - 4 STORE - 12 ADD - 4 MUL LD LD LD LD 2LD 2LD 2LD 2LD L ST ST ST ST * * * * core execution: 12 cy 14

14 Example 1: 2D Jacobi in DP with SSE2 on SNB Situation 1: Data set fits into L1 cache ECM prediction: (8 LUP / 12 cy) * 3.5 GHz = 2.3 GLUP/s Measurement: 2.2 GLUP/s 12 cy Situation 2: Data set fits into L2 cache (not into L1) 3 additional transfer streams from L2 to L1 (data delay) ECM prediction: (8 LUP / (12+6) cy) * 3.5 GHz = 1.5 GLUP/s t1 RFO t0 6 cy Measurement: 1.9 GLUP/s Overlap? 15

15 Example 1: 2D Jacobi in DP with SSE2 on SNB LD LD LD LD 2LD 2LD 2LD 2LD L ST ST ST ST * * * * core execution: 12 cycles L1 single ported no overlap during LD/ST data delay: 6 cycles ECM prediction w/ overlap: (8 LUP / (8.5+6) cy) * 3.5 GHz = 1.9 GLUP/s Measurement: 1.9 GLUP/s 12 cy t1 RFO t0 6 cy If the model fails, we learn something 16

16 Example 2: A 3D Jacobi smoother with AVX vectorization on an Intel Ivy Bridge processor 17

17 Jacobi 3D Manual Analysis Operation Count (1 LUP) MUL 1 ADD 5 LOAD 6 STORE 1 Cycle Count (4x unroll + AVX = 16 LUP) MUL 4 ADD 20 LOAD 24 STORE 8 18

18 Interlude: Intel Architecture Code Analyzer (IACA) Performs architecture-specific code analysis Prerequisite: Mark start and end of dominant work loop In high-level code (documented) In assembly code (see iacamarks.h) Does not influence code optimization (e.g. vectorization) Assembly loop might perform multiple updates per iteration (unrolling, SIMD) Important reports (throughput mode): Block throughput: runtime of one loop iteration ( core-time) Throughput bottleneck: limiting resource for code execution Port pressure: dominant pipeline port 19

19 16 updates (4x unroll + AVX) = 2 cache lines per loop iteration #pragma vector aligned 20

20 M-L3 (12cy) L3-L2 (10cy) L2-L1 (10cy) ADD (10cy) L1-REG (LD 12cy) Jacobi 3D overlap ivyep1 Non-LD/ST time Intel(R) Xeon(R) CPU E GHz Memory Bandwidth 47 GB/s Data transfers FrontEnd stalls 0.5*( ) =0.05cy MUL (2cy) Reg-Reg (6cy) Stores (4cy) Times [cy] for 8 LUP (DP) = 1 CL update = 0.5 loop iterations (ASM) = 0.5 * IACA output IACA throughput: 24.1cy/16LUP Single-core performance 3.0GHz / (44cy/ 8LUP) = 545MLUP/s Measurement (N=400): 542MLUP/s (~44cy) 44cy #pragma vector aligned 21

21 Socket Scaling ivyep1 Intel(R) Xeon(R) CPU E GHz Memory Bandwidth 47 GB/s 23

22 Example 3: 3D long-range stencil in single precision with AVX on Sandy Bridge 24

23 Example 2: 3D long-range stencil in SP with AVX on SNB Core execution 4 neighbors per direction Operations per update (code) 27 LOAD (25 V, 1 ROC, 1 U) 1 STORE (U) 26 ADD 15 MUL Core time & actual LOAD count IACA Collaboration with D. Keyes & T. Malas (KAUST) 25

24 IACA example output Core execution Core Execution time (16 LUP) = 2*34.25 cy = 68.5 cy Data transfer: LOAD ports REG L1: 2*30.5 cy = 61 cy 128 Bit Loads AVX vectorization, no unrolling: One iteration updates 8 SP (float) elements Multiply all numbers by 2X to get time for updating 1 CacheLine (16 floats) 26

25 Example 2: Data delay Problem size: (single precision) cy/cl Layer condition at L3: OK & V(0:imax,j-4:j+4,k) fits L1 cache 61 cy From IACA analysis 8 LOADS to V can be served directly by L3 cache + 1 from main memory 24 cy 24 cy 17 cy MemBW=40 GB/s Minimum data transfer to main memory: 4 WORD/LUP (LD: U,V,ROC ST:U) 27

26 M-L3 17 cy L3-L2 24 cy L2-L1 24 cy 126 cy ADD 52 cy MULT 38 cy Reg-Reg transfers 48cy L1-REG (Load) 61 cy Example 2: Putting all together Core execution (Non-LD/ST cycles) Data delay Stores 4cy IACA throughput 68.5 cy / CL (sp) FrontEnd stalls overlap: ( ) cy =7.5cy Single-core performance (ECM Model) 2.7GHz / (126cy / 16LUP) = 343 MLUP/s Measurement: 320 MLUP/s

27 Socket scaling memory bandwidth limit 30

28 ECM model: Conclusions & outlook Saturation effects are ubiquitous; understanding them gives us opportunity to Find out about optimization opportunities Save energy by letting cores idle see power model later on Putting idle cores to better use see spmvm case study Simple models work best. Do not try to complicate things unless it is really necessary! Possible extensions to the ECM model Accommodate latency effects Model simple architectural hazards 36