How tiling works in matrix multiplication — loading blocks into shared memory

Why most transformer operations are memory-bound, not compute-bound

Transformer operations rely heavily on matrix multiplications, which are memory-intensive tasks

Why memory coalescing matters — adjacent threads reading adjacent memory addresses

Memory coalescing reduces cache misses, improving multithreaded application performance

How do lock-free data structures manage concurrent access to shared memory in a multithreaded environment?

Lock-free data structures use atomic operations to ensure concurrent access without traditional locking mechanisms

How KV-cache reduces redundant computation in autoregressive generation

KV-cache minimizes redundant computations by storing intermediate results in autoregressive models

What LSM trees optimize: write-heavy workloads by buffering writes in memory

LSM trees optimize write-heavy workloads through in-memory buffering

What operator fusion does at the compiler level: merges adjacent ops to reduce memory traffic

Operator fusion optimizes code by combining adjacent operations into a single instruction, minimizing memory access