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💾 Memory Allocators
Heap Management, jemalloc, Performance, Fragmentation
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112197
posts in
379.2
ms
PAM: Processing Across Memory
Hierarchy
for Efficient
KV-centric
LLM Serving System
arxiv.org
·
9h
🧠
PIM
Benchmarking for Single Feature Attribution with
Microarchitecture
Cliffs
arxiv.org
·
9h
📊
Profile-Guided Optimization
Evaluating Claude’s C
Compiler
Against
GCC
shbhmrzd.github.io
·
1d
·
Discuss:
r/C_Programming
🔗
GCC Link-Time Optimization
Completed
Hyperparameter
Transfer across Modules, Width, Depth, Batch and
Duration
machinelearning.apple.com
·
14h
🤖
TVM
Why the
M5
Matters If You Run AI
Locally
macsparky.com
·
53m
🧩
mimalloc
AI in Multiple
GPUs
: Understanding the Host and Device
Paradigm
towardsdatascience.com
·
1d
🔥
PyTorch
C++20 matching engine - arena allocator, lock-free
SPSC
, intrusive linked lists, 255ns
p50
latency
github.com
·
9h
·
Discuss:
r/cpp
⚙️
LMAX Architecture
Supercharging
Inference for AI Factories: KV Cache
Offload
as a Memory-Hierarchy Problem
blog.min.io
·
1d
🧱
Slab Allocation
Moltis
: Rust based AI assistant with memory, tools, and
self-extending
skills
moltis.org
·
19h
·
Discuss:
Hacker News
🦀
Rust
The system
statistics
collection
daemon
collectd.org
·
1d
📈
Prometheus
Introducing GPT‑5.3‑
Codex
‑
Spark
simonwillison.net
·
17h
🎯
Lance
Hacker
Newsletter
#782
buttondown.com
·
2h
🐛
Fuzzing
Anubis
OSS
— Local LLM Benchmarking for Apple Silicon
devpadapp.com
·
3d
·
Discuss:
r/opensource
⚙️
Performance Profiling
Optimizing the
MongoDB
Java Driver: How minor
optimizations
led to macro gains
linkedin.com
·
1d
·
Discuss:
DEV
📄
FlatBuffers
Discussion - Investigation of Single Thread CPU "
Thoughput/cycle
"
forums.anandtech.com
·
1d
⚙️
Performance Profiling
MiniMaxAI
MiniMax-M2.5 has
230b
parameters and 10b active parameters
openhands.dev
·
17h
·
Discuss:
r/LocalLLaMA
🚀
Performance
Creeping
memory
allocation
community.folivora.ai
·
5d
🏛️
Region-Based Memory
5 Days, One GPU
Gameboy
Swarm
bkase.io
·
41m
·
Discuss:
Hacker News
⚡
Hardware Acceleration
Minimum
Energy Per
Query
semiengineering.com
·
1d
⏪
Deoptimization
Nvidia’s new
technique
cuts LLM reasoning costs by 8x without losing
accuracy
venturebeat.com
·
16h
🚀
Milvus
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