Scale-out Computing Model on Massive Core System: From HPC ... · Scale-out Computing Model on Massive Core System: From HPC to Fabric-Based SoC Dr. Fu Li [email protected] Quantum Cloud

Scale-out Computing Model on Massive Core System: From HPC to Fabric-Based SoC

Dr. Fu Li [email protected]

Quantum Cloud Future (Beijing) Technologies Co., Ltd.

Quantum Cloud Future (Beijing) Technology Co. Ltd.

Cook Book

1. What is Massive Core System (MCS)? 1.1. HPC system 1.2. GPU system 1.3. MicroSlides: Fabric-based SoC

2. Why scale-out computing is important in MCS? 3. How to make MCS faster?

3.1. MPI and openMP in HPC 3.2. Memory coalescing and cudaDMA in GPU computing

4. QCF’s scale-out computing model for Microslides 4.1. the hardware (Socionext) 4.2. the architecture 4.3. the result (arm vs x86 vs GPU)

new


Quantum Theory and SpectroscopyMolecular Dynamics Fast Fourier Transform

HPC

Content-Centric Networking

Cloud StorageDoppler ASIC Boba FPGA

MPI, OpenMP CUDAStatistic MechanicsGPU switch

PacketShader

Introduction to Quantum Cloud

With background from Quantum calculation, 1) we perform large-scale molecular dynamics simulation on HPC cluster using

Amber and Gromacs, 2) we optimize Fourier transform and matrix operation on multicore system.



Then we found GPU is a great tool for both molecular dynamics and matrix operation.



Later we found similar systems with massive CPU cores.



Today we will show some practical example about our scale-out algorithm on these systems


Num

ber o

f Cor

es

1

10

100

1,000

10,000

100,000

System Power Consumption (Watts)10 100 1000 10K 100k 1M

System and Cores: Communication Matters

QCF & SOCIONEXT

PC Server

Blade Server

Super Computer

General-purpose


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es

1

10

100

1,000

10,000

100,000



QCF & SOCIONEXT

PC Server

Blade Server

Super Computer

GPU

GPU Cluster

General-purpose

Special-purpose


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es

1

10

100

1,000

10,000

100,000



QCF & SOCIONEXT

PC Server

Blade Server

Super Computer

GPU

GPU Cluster

General-purpose

Special-purpose

Traditional ARM Server

ARM SoC


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f Cor

es

1

10

100

1,000

10,000

100,000



QCF & SOCIONEXT

PC Server

Blade Server

Super Computer

GPU

GPU ClusterMicroslides

Special-purpose

General-purpose

General-purpose

Microslides of ARM CPU

Microslides of ARM SoC


ARM SoC


Num

ber o

f Cor

es

1

10

100

1,000

10,000

100,000



QCF & SOCIONEXT

PC Server

Blade Server

Super Computer

GPU

GPU ClusterMicroslides

Microslides of ARM CPU

Microslides of ARM SoC

2006 20182012

intra CPU connectioninter CPU connectioncluster connection

Special-purpose

General-purpose

General-purpose


ARM SoC


Data Communication Between Systems Is Obstacle

cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1

cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1

Cache/Storage

I/O

Hierarchical structure is critical for Von Neumann architecture



cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1

cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1

Cache/Storage

I/O



cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1

cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1instruction-level parallelism

OS-level parallelism

algorithm-level parallelism

Cache/Storage

I/O



cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1

cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3




batch, share-nothing stateless computing

big RAM avoid context switching TLB, cache-conscious

big.LITTLE GPU, FPGA

Fast cache, cache prefetch Vector processing, SIMD/AVX

Cache/Storage

I/O



cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3

Cache L1

cores

Intra CPU Fabric

Sockets Bus

Memory

Networking

Cache L2/L3




batch, share-nothing stateless computing

big RAM avoid context switching TLB, cache-conscious

big.LITTLE GPU, FPGA

Fast cache, cache prefetch Vector processing, SIMD/AVX

Cache/Storage

I/O

Consolidation will be the next-wave innovation for Chip design and system optimization • IO consolidation: networking, bus, fabric • storage consolidation: memory, cache, networking buffer


Parallel and Scaling


Fabric-Based ARM SoC

From SOCIONEXT

• PCIe Fabric for networking • 768 cores • c2c 10Gbps, 36 microsec latency • 1TB DDR4 RAM • 700 watts TDP per chassis

watt/coreARM SoC 1

x86 16 ~ 25GPU 0.3~0.5


Cluster Management Tools

PBS openstack kubernetes mesos

basic batch process kvm container container/noncontainer

provery fast

very flexible normally with MPI

very secure very stable

system-level isolation

fast secure

production ready

fast compatible with

process and container production ready

can be securecons no isolation high overhead slow

container app not flexible enough complexity

scenario scientific calculation private cloud application CI Datacenter OS


Share-Nothing + Message Queue Architecture

Stateless 计算架构

host

core core IO core use an “individual” core to do IO for the host to increase the throughput


Example: PacketShader on GPU


Example: Rendering on Arm

Render@Baremetal

Render@Container

0

1

2

3

4

buggy fishy cat bmps teeglasFX splash poked

Intel ARM

0

0.5

1

1.5

2

bmw27 classroom bechmark

Baremetal 1container 2container 4container

并发情况下提⾼高3倍

多实例例并发情况下提⾼高1.8倍


Example: Rendering on Arm

0

7.5

15

22.5

30

performace scaled 1 scaled 2Intel arm SoC Intel arm SoC Intel arm SoC

scaled 1: scaled performance with frequency and core number scaled 2: scaled performance with frequency and core number and watts


Example: AI on Arm

Caffe@Container ARM vs Intel vs GPU (scaled)

0

0.4

0.8

1.2

1.6

CIFAR 10 - 1 CIFAR 10 -2 CIFAR 10 - 3

Intel ARM GPU 1070


Example: AI on Arm SoC

048

1216

caffe scaled caffe darknet scaled darknetIntel SoC Intel SoC Intel SoC Intel SoC

02.254.5

6.759

caffe scaled caffe darknet scaled darknetIntel SoC Intel SoC Intel SoC Intel SoC

Training

Inference

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Documents

Scale-out Computing Model on Massive Core System: From HPC ... · Scale-out Computing Model on Massive Core System: From HPC to Fabric-Based SoC Dr. Fu Li [email protected] Quantum Cloud