Ron Swartzentruber, Director of Engineering at Lightelligence, explains why optical connectivity is needed for CXL fabrics, and provides an overview of the Photowave line of port expander PCIe cards and active optical cables.
Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya Halder
Q1 Memory Fabric Forum: Advantages of Optical CXL for Disaggregated Compute Architectures
1. Harnessing light to power new possibilities
Advantages of Optical CXL
for Disaggregated Compute Architectures
Ron Swartzentruber
Director of Engineering
Key message: CXL is industry consensus for disaggregation
MemVerge policy: System memory 60%, CXL Memory 40%
What is CPU%
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CPU%
mem 29.525
cxl 31.431000000000004
disk 81.46
main.py:36: MatplotlibDeprecationWarning: Calling gca() with keyword arguments was deprecated in Matplotlib 3.4. Starting two minor releases later, gca() will take no keyword arguments. The gca() function should only be used to get the current axes, or if no axes exist, create new axes with default keyword arguments. To create a new axes with non-default arguments, use plt.axes() or plt.subplot().
ax = plt.gca(facecolor='black')
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MEM%
mem 27.2
cxl 27.2
disk 11.722000000000001
********************************************************************************
GPU%
mem 99.49
cxl 97.05
disk 53.01
********************************************************************************
CXLMEM%
mem 0.0016306192454823602
cxl 77.11430249904593
disk 0.1663918208702139
********************************************************************************
GPUMEM%
mem 45.17
cxl 49.0
disk 34.71
********************************************************************************
GPUMEM_USED_MB
mem 9213.4375
cxl 9213.4375
disk 8979.4375
********************************************************************************
PCI_TX_MBps
mem 274.2578125
cxl 191.357421875
disk 81.064453125
********************************************************************************
PCI_RX_MBps
mem 2007.3828125
cxl 1422.421875
disk 1158.056640625
(tfpy38) hussainazhar@Hussains-MacBook-Air T4gpu % python main.py
********************************************************************************
CPU%
mem 29.525
cxl 31.431000000000004
disk 81.46
main.py:36: MatplotlibDeprecationWarning: Calling gca() with keyword arguments was deprecated in Matplotlib 3.4. Starting two minor releases later, gca() will take no keyword arguments. The gca() function should only be used to get the current axes, or if no axes exist, create new axes with default keyword arguments. To create a new axes with non-default arguments, use plt.axes() or plt.subplot().
ax = plt.gca(facecolor='black')
********************************************************************************
MEM%
mem 27.2
cxl 27.2
disk 11.722000000000001
********************************************************************************
GPU%
mem 99.49
cxl 97.05
disk 53.01
********************************************************************************
CXLMEM%
mem 0.0016306192454823602
cxl 77.11430249904593
disk 0.1663918208702139
********************************************************************************
GPUMEM%
mem 45.17
cxl 49.0
disk 34.71
********************************************************************************
GPUMEM_USED_MB
mem 9213.4375
cxl 9213.4375
disk 8979.4375
********************************************************************************
PCI_TX_MBps
mem 274.2578125
cxl 191.357421875
disk 81.064453125
********************************************************************************
PCI_RX_MBps
mem 2007.3828125
cxl 1422.421875
disk 1158.056640625