master-thesis-presentation/slides/simulations.md

Simulations

Microbenchmarks

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• Vector benchmarks (BLAS level 1)

  • VADD: z = x + y
  • VMUL: z = x \cdot y
  • HAXPY: z = a \cdot x + y

• Vector-Matrix benchmarks (BLAS level 2)

  • GEMV: z = A \cdot x
  • Simple DNN:
    • f(x) = z = ReLU(A \cdot x)
    • z_{n+1} = f(z_n)
    • 5 layers in total

Level	Vector	GEMV	DNN
X1	(2M)	(1024 x 4096)	(256 x 256)
X2	(4M)	(2048 x 4096)	(512 x 512)
X3	(8M)	(4096 x 8192)	(1024 x 1024)
X4	(16M)	(4096 x 8192)	(2048 x 2048)

Operand Dimensions

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Simulations

System Configuration

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Two simulated systems:

• Generic ARM system
• Infinite compute system
  • completely memory bound

Two real GPUs using HBM2:

• AMD RX Vega 56
• NVIDIA V100

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layout: figure figureUrl: /speedup_normal.svg figureCaption: Speedups of PIM compared to non-PIM

Simulations

Speedups / Generic ARM System

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layout: figure figureUrl: /speedup_inf.svg figureCaption: Speedups of PIM compared to non-PIM

Simulations

Speedups / Infinite Compute System

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layout: figure figureUrl: /samsung.svg figureCaption: Speedups of Samsung for VADD and GEMV

Simulations

Speedups / Samsung

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Lee et al. „Hardware Architecture and Software Stack for PIM Based on Commercial DRAM Technology : Industrial Product“, 2021.

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layout: figure figureUrl: /runtimes_vector.svg figureCaption: Runtimes for Vector Benchmarks

Simulations

Runtimes / Vector Benchmarks

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layout: figure figureUrl: /runtimes_matrix.svg figureCaption: Runtimes for Matrix Benchmarks

Simulations

Runtimes / Matrix Benchmarks

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