Lmst

Unlocking the Power of VLSI in Automotive and Embedded Systems

Join yours Educational open Source community
👉 Download Now from Google Play
🔗 https://play.google.com/store/apps/details?id=com.piembsystech&pcampaignid=web_share
👉 Visit for more :
🌎 https://piembsystech.com/basic-understanding-of-vlsi/

#VLSIDesign #EmbeddedSystems #AutomotiveElectronics #ChipDesign #SystemOnChip #CMOSTechnology #SemiconductorEngineering #ECUDevelopment #ADAS #BMS #VehicleNetworking #ASICDesign #RTLDesign #MicrocontrollerDesign #HardwareArchitecture #AutomotiveSoftware #LowLevelProgramming

Analyzing Modern NVIDIA GPU cores

#HardwareArchitecture

https://hgpu.org/?p=29837

@jfmezei One of the reasons VAX is comparatively slow involves the condition codes, including the carry bit.

~Every VAX instruction is a test instruction, if you want it to be.

But if you break that part of the VAX design to make the architecture go faster, you might as well also break, err, alter some other VAX architectural design constraints. After some other work including Prism, that architectural replacement was Alpha.

As assemblers go, VAX is quite nice.

But assembler as a choice for app development started to fade around the era of the 3GL vs Assembler debates; the early to mid 1980s.

Section 8.4 has details of the VAX condition codes:

https://docs.vmssoftware.com/docs/vsi-openvms-vax-macro-and-instruction-set-reference-manual.pdf#page156

#vax #hardwarearchitecture #retrocomputing

Good things come in small packages: Should we adopt Lite-GPUs in AI infrastructure?

#AI #HardwareArchitecture

https://hgpu.org/?p=29704

A survey on FPGA-based accelerator for ML models

#FPGA #Survey #MachineLearning #ML #HardwareArchitecture

https://hgpu.org/?p=29622

Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems