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EC2 Accelerated Computing Instances

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AWS EC2 Accelerated Computing Instances

Accelerated computing instances are mostly utilized by companies who make use of the following:

– Hardware accelerators

– Co-processors

– Functions

– Floating point number calculations

– Graphics processing

– Data pattern matching,

These operations are even performed more efficiently and effectively than what other software running on CPUs are capable of.

 

P3:

EC2 Accelerated Computing Instances - P3

EC2 Accelerated Computing Instances – P3

They are the newest generation of general-purpose GPU instances.

Its Features Include:

  • 8 NVIDIA Tesla V100 GPUs [pairing 5,120 CUDA Cores + 640 Tensor Cores]
  • Intel Xeon E5-2686 v4 [High frequency] processors (p3.2xlarge+ p3.8xlarge + p3.16xlarge)
  • 5 GHz Intel Xeon P-8175M [High frequency] processors (p3dn.24xlarge)
  • NVLink: peer-to-peer GPU communication
  • Offer 100 Gbps aggregate network bandwidth
  • EFA: p3dn.24xlarge instances

 

Instance GPUs vCPU Mem (GiB) GPU Mem (GiB) GPU P2P Storage (GB) Dedicated EBS Bandwidth Networking Performance
p3.2xlarge 1 8 61 16 EBS-Only 1.5 Gbps Up to 10 Gigabit
p3.8xlarge 4 32 244 64 NVLink EBS-Only 7 Gbps 10 Gigabit
p3.16xlarge 8 64 488 128 NVLink EBS-Only 14 Gbps 25 Gigabit
p3dn.24xlarge 8 96 768 256 NVLink 2 x 900 NVMe SSD 19 Gbps 100 Gigabit

Every instance has the bellow specs:

  • Intel AVX + Intel AVX2 + Intel Turbo
  • It is EBS Optimized
  • It has Enhanced Networking

 

p3.2xlarge + p3.8xlarge + p3.16xlarge: include 2.3 GHz and 2.7 GHz Intel Xeon E5-2686 v4 processors.

p3dn.24xlarge: 2.5 GHz and 3.1 GHz Intel Xeon P-8175M processors + supports Intel AVX-512.

p3dn.24xlarge: EFA that allows for HPC apps that use the MPI and ML apps through NCCL for scaling to thousands of GPUs.

Used for the below Cases:

– Machine/Deep learning

– High performance computing

– Computational fluid dynamics

– Computational finance

– Seismic analysis

– Speech recognition

– Autonomous vehicles

– Drug discovery

 

 

P2:

EC2 Accelerated Computing Instances - P2

EC2 Accelerated Computing Instances – P2

Those instances are made specifically for general-purpose GPU compute apps.

Its Features Include:

  • Intel Xeon E5-2686 v4 processors (High freq.)
  • NVIDIA K80 GPUs (High-performance) (2,496 parallel processing cores + 12GiB GPU memory)
  • Works with GPUDirect™ peer-to-peer GPU communications
  • Offers Enhanced Networking through ENA (25 Gbps aggregate network bandwidth) within a Placement Group
  • It is by default EBS-optimized for no extra cost
Instance GPUs vCPU Mem (GiB) GPU Memory (GiB) Network Performance
p2.xlarge 1 4 61 12 High
p2.8xlarge 8 32 488 96 10 Gigabit
p2.16xlarge 16 64 732 192 25 Gigabit

Every instance has the bellow specs:

  • 2.3 GHz + 2.7 GHz Intel Xeon E5-2686 v4 Processor
  • Intel AVX + Intel AVX2 + Intel Turbo
  • It is EBS Optimized
  • It has Enhanced Networking

Used in the following Cases:

– Machine learning

– High performance databases

– Computational fluid dynamics

– Computational finance

– Seismic analysis

– Molecular modeling

– Genomics

– Rendering

– Other server-side GPU compute workloads

 

Inf1:

EC2 Accelerated Computing Instances - INF1

EC2 Accelerated Computing Instances – INF1

These instances are made up from the ground up for the goal of supporting machine learning inference apps.

Its Features Include:

  • 16 Inferentia Chips
  • Neuron SDK
  • Second Gen Intel® Xeon® Scalable processors (High Frequency)
  • 100 Gbps networking
Instance size vCPUs Memory (GiB) Storage Inferentia chips Inferentia chip-to-chip interconnect Network bandwidth EBS bandwidth
inf1.xlarge 4 8 EBS only 1 N/A Up to 25 Gbps Up to 4.75 Gbps
inf1.2xlarge 8 16 EBS only 1 N/A Up to 25 Gbps Up to 4.75 Gbps
inf1.6xlarge 24 48 EBS only 4 Yes 25 Gbps 4.75 Gbps
inf1.24xlarge 96 192 EBS only 16 Yes 100 Gbps 19 Gbps

 

Used in the below Cases:

– Recommendation engines

– Forecasting

– Image and video analysis

– Advanced text analytics

– Document analysis

– Voice

– Conversational agents

– Translation

– Transcription

– Fraud detection

 

G4:

EC2 Accelerated Computing Instances - G4

EC2 Accelerated Computing Instances – G4

These instances are developed for the sake of aiding the acceleration of machine learning inference + graphics-intensive workloads.

Its Features Include:

  • Second Generation Intel Xeon Scalable processors
  • NVIDIA T4 Tensor Core (GPUs)
  • 100 Gbps networking throughput
  • 8 TB local NVMe storage
Instance GPUs vCPU Mem (GB) GPU Memory (GB) Instance Storage (GB) Network Performance (Gbps)
Single GPU VMs g4dn.xlarge 1 4 16 16 125 Up to 25
g4dn.2xlarge 1 8 32 16 225 Up to 25
g4dn.4xlarge 1 16 64 16 225 Up to 25
g4dn.8xlarge 1 32 128 16 1×900 50
g4dn.16xlarge 1 64 256 16 1×900 50
Multi GPU VMs g4dn.12xlarge 4 48 192 64 1×900 50
g4dn.metal* 8 96 384 128 2×900 100

Every instance has the below specs:

  • Cascade Lake 24C processors (2.5 GHz)
  • Intel AVX + Intel AVX2 + Intel AVX-512 + Intel Turbo
  • It is EBS Optimized
  • It has Enhanced Networking

Used in the following Cases:

Machine learning inference for apps such as:

– The addition of metadata to an image

– Object detection

– Recommender systems

– Automated speech recognition

– Language translation

Those instances offer a truly cost-efficient platform for the sake of building + running graphics-intensive apps, including:

– Remote graphics workstations

– Video transcoding

– Photo-realistic design

– Game streaming in the cloud

 

G3:

EC2 Accelerated Computing Instances - G3

EC2 Accelerated Computing Instances – G3

They are specifically developed for graphics-intensive apps.

Its Features Include:

  • Intel Xeon E5-2686 v4 processors (High Frequency)
  • NVIDIA Tesla M60 GPUs, every one of which has 2048 parallel processing cores + 8 GiB video memory
  • Allows for NVIDIA GRID Virtual Workstation features
  • Supports 4 monitors + resolutions 4096×2160
  • Every GPU found in the instance is licensed for 1 Concurrent Connected User
  • Allows NVIDIA GRID Virtual Application abilities for app virtualization software
  • Supports 25 concurrent users/GPU
  • Every one of the GPU features an on-board hardware video encoder
  • Supports 10 H.265 1080p30 streams + 18 H.264 1080p30 streams
  • Allows low-latency frame capture + encoding
  • Experiences with high-quality interactive streaming
  • Enhanced Networking: ENA + 25 Gbps of aggregate network bandwidth (Placement Group)
Instance GPUs vCPU Mem (GiB) GPU Memory (GiB) Network Performance
g3s.xlarge 1 4 30.5 8 Up to 10 Gigabit
g3.4xlarge 1 16 122 8 Up to 10 Gigabit
g3.8xlarge 2 32 244 16 10 Gigabit
g3.16xlarge 4 64 488 32 25 Gigabit

Every instance has the below specs:

  • 2.3 GHz + 2.7 GHz  Intel Xeon E5-2686 v4 Processor
  • Intel AVX + Intel AVX2 + Intel Turbo
  • It is EBS Optimized
  • It has Enhanced Networking

Used in the below Cases:

– 3D visualizations

– Graphics-intensive remote workstation

– 3D rendering

– App streaming

– Video encoding

– Other server-side graphics workloads.

 

F1:

EC2 Accelerated Computing Instances - F1

EC2 Accelerated Computing Instances – F1

This type of instances provides customizable hardware acceleration going along with some FPGAs.

Its Instances Features Include:

  • Intel Xeon E5-2686 v4 (High frequency) processors
  • NVMe SSD Storage
  • Enhanced Networking

Its FPGA Features Include:

  • Xilinx Virtex UltraScale+ (VU9P FPGAs)
  • 64 GiB of ECC-protected memory (4x DDR4)
  • PCI-Express (x16 interface)
  • About 2.5 mill logic elements
  • About 6,800 DSP engines
  • FPGA Developer (AMI)
Instance FPGAs vCPU Mem (GiB) SSD Storage (GB) Networking Performance
f1.2xlarge 1 8 122 470 Up to 10 Gigabit
f1.4xlarge 2 16 244 940 Up to 10 Gigabit
f1.16xlarge 8 64 976 4 x 940 25 Gigabit

f1.16xlarge instances: PCI-e fabric allows the FPGAs to share the exact memory space + communicate with one another throughout the fabric at 12 Gbps in every direction.

Every instance has the below specs:

  • 2.3 GHz + 2.7 GHz Intel Xeon E5-2686 v4 Processor
  • Intel AVX + Intel AVX2 + Intel Turbo
  • It is EBS Optimized
  • It has Enhanced Networking

Used in the following Cases:

– Genomics research

– Financial analytics

– Real-time video processing

– Big data search + analysis + security

ec2 storage optimized instances

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