A5042558892- Parallel Computing and Optimization Techniques
- Stochastic Gradient Optimization Techniques
- Ferroelectric and Negative Capacitance Devices
- Advanced Neural Network Applications
- Low-power high-performance VLSI design
Meta (United States)
2023
This paper presents the design of Glow, a machine learning compiler for heterogeneous hardware. It is pragmatic approach to compilation that enables generation highly optimized code multiple targets. Glow lowers traditional neural network dataflow graph into two-phase strongly-typed intermediate representation. The high-level representation allows optimizer perform domain-specific optimizations. lower-level instruction-based address-only memory-related optimizations, such as instruction...
Meta has traditionally relied on using CPU-based servers for running inference workloads, specifically Deep Learning Recommendation Models (DLRM), but the increasing compute and memory requirements of these models have pushed company towards specialized solutions such as GPUs or other hardware accelerators. This paper describes company's effort in constructing its first silicon designed recommendation systems; it accelerator architecture platform design, software stack enabling optimizing...