Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...

Abstract: Current DRAM-based memory systems face the scalability challenges in terms of memory density, energy consumption, and monetary cost. Hybrid memory architectures composed of emerging ...

Python does include another native way to run a workload across multiple CPUs. The multiprocessing module spins up multiple copies of the Python interpreter, each on a separate core, and provides ...

Hello Pythonistas welcome back. Python is a simple yet interesting language. Today we will take a deep dive into one of its interesting feature __pycache__ folder. Before diving into the concept let ...

I have workers which require access to a several GBs sized read only cache to do various things. When I left the cache as a global variable, joblib was very slow, so I started loading them from pickle ...

from functools import partial from joblib import Memory mem = Memory(cache_dir, verbose=0) def foo(a: str, b: str): msg = f"a={a}, b={b}" print(f"foo called with {msg ...

Abstract: The need of faster access-times and increased memory bandwidths has triggered a concerted research effort towards deploying optical memory circuitry, targeting at the apex of the memory ...