Add: more Phoenix flavor

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---
title: Ace Profiling Attorney - The Case of the Missing Gbits
categories: [Programming, Profiling]
tags: [Rust, kernel, networking]
---
> **Cast**
>
> **Me:** “I rewrote a port forwarder in Rust. It works. Its… not fast enough.”
>
> **Inner Prosecutor:** “*Objection!* Not fast enough is not evidence. Bring numbers.”
>
> **Me:** “Fine. Well do this properly.”
---
## 0. The Situation
Im building a userspace TCP port forwarder in Rust called [oxidinetd](https://github.com/DaZuo0122/oxidinetd) (The binary named `oi`). It accepts a TCP connection, connects to an upstream server, then relays bytes in both directions.
> This post is not a “Rust vs C” piece — its about **profiling**, **forming hypotheses**, and **turning measurements into speed**.
### Test environment
- OS: Debian 13
- Kernel: `6.12.48+deb13-amd64`
- Runtime: `smol`
- Benchmark: single machine, network namespaces + veth
Why namespaces + veth? The loopback can hide “real networking” behavior. Namespaces/veth keep the test local (repeatable), but with a path closer to real routing.
---
> **Inner Prosecutor:** “You claim its repeatable. Prove your setup.”
>
> **Me:** “Heres the lab.”
---
## 1. The Lab Setup
Backend server inside `ns_server`:
```bash
sudo ip netns exec ns_server iperf3 -s -p 9001
```
Client inside `ns_client`, traffic goes through `oi`:
```bash
sudo ip netns exec ns_client iperf3 -c 10.0.1.1 -p 9000 -t 30 -P 8
```
> **Note**: -P 8 matters. A forwarder might look okay under -P 1, then collapse when syscall pressure scales with concurrency.
### Forwarder config
`oi` listens on `10.0.1.1:9000` and connects to `10.0.0.2:9001`.
`profiling.conf`:
```yaml
127.0.0.1 9000 127.0.0.1 9001
```
---
## 2. The Questions
> **Inner Prosecutor:** “Alright. What exactly is the crime?”
>
> **Me:** “Throughput is lower than expected. The suspects:”
>
> 1. CPU bound vs I/O bound
> 2. Userspace overhead vs kernel TCP stack
> 3. Syscall-rate wall (too many `send/recv` per byte)
> 4. Async runtime scheduling / wakeups / locks
---
## 3. Evidence Tool #1 — `perf stat` (Macro view)
Command:
```bash
sudo perf stat -p $(pidof oi) -e \
cycles,instructions,cache-misses,branches,branch-misses,context-switches,cpu-migrations \
-- sleep 33
```
### What Im looking for
* **Context switches** exploding → runtime contention or wake storms
* **CPU migrations** exploding → scheduler instability (bad for repeatability)
* **IPC** tanking + cache misses skyrocketing → memory/latency issues
* Otherwise: likely **kernel networking + syscalls** dominate
Output:
```text
Performance counter stats for process id '209785':
113,810,599,893 cpu_atom/cycles/ (0.11%)
164,681,878,450 cpu_core/cycles/ (99.89%)
102,575,167,734 cpu_atom/instructions/ # 0.90 insn per cycle (0.11%)
237,094,207,911 cpu_core/instructions/ # 1.44 insn per cycle (99.89%)
33,093,338 cpu_atom/cache-misses/ (0.11%)
5,381,441 cpu_core/cache-misses/ (99.89%)
20,012,975,873 cpu_atom/branches/ (0.11%)
46,120,077,111 cpu_core/branches/ (99.89%)
211,767,555 cpu_atom/branch-misses/ # 1.06% of all branches (0.11%)
245,969,685 cpu_core/branch-misses/ # 0.53% of all branches (99.89%)
1,686 context-switches
150 cpu-migrations
33.004363800 seconds time elapsed
```
Interpretation:
**Low context switching**:
- context-switches: 1,686 over ~33s → ~51 switches/sec
- cpu-migrations: 150 over ~33s → ~4.5/s → very stable CPU placement
**CPU is working hard**:
- 237,094,207,911 cpu_core instructions
- IPC: 1.44 (instructions per cycle) → not lock-bound or stalling badly
**Clean cache, branch metrics**:
- cache-misses: ~3.1M (tiny compared to the instruction count)
- branch-misses: 0.62%
---
> **Inner Prosecutor:** “Thats a vibe-check. Wheres the real culprit?”
>
> **Me:** “Next tool. This one tells me what kind of pain were paying for.”
---
## 4. Evidence Tool #2 — `strace -c` (Syscall composition)
Command:
```bash
sudo timeout 30s strace -c -f -p $(pidof oi)
```
### Why `strace -c` is lethal for forwarders
A userspace TCP forwarder often boils down to:
* `recv(...)` from one socket
* `send(...)` to the other socket
If your throughput is low and `strace -c` shows **millions** of `sendto/recvfrom` calls, youre likely hitting a **syscall-per-byte wall**.
Output (simplified):
```text
sendto 2,190,751 calls 4.146799s (57.6%)
recvfrom 2,190,763 calls 3.052340s (42.4%)
total syscall time: 7.200789s
```
Interpretation:
(A) **100% syscall/copy dominated:**
Almost all traced time is inside:
- sendto() (TCP send)
- recvfrom() (TCP recv)
(B) **syscall rate is massive**
Total send+recv calls:
- ~4,381,500 syscalls in ~32s
- → ~137k `sendto` per sec + ~137k `recvfrom` per sec
- → ~274k syscalls/sec total
Thats exactly the pattern of a forwarder doing:
`recv -> send -> recv -> send ...` with a relatively small buffer.
---
> **Inner Prosecutor:** “So youre saying the kernel is being spammed.”
>
> **Me:** “Exactly. Now I want to know whos spamming it — my logic, my runtime, or my copy loop.”
---
## 5. Evidence Tool #3 — FlameGraph (Where cycles actually go)
Commands:
```bash
sudo perf record -F 199 --call-graph dwarf,16384 -p $(pidof oi) -- sleep 30
sudo perf script | stackcollapse-perf.pl | flamegraph.pl > oi.svg
```
### What the flamegraph showed (described, not embedded)
Instead of embedding the graph, heres the important story the flamegraph told:
1. The widest “towers” were kernel TCP send/recv paths:
* `__x64_sys_sendto``tcp_sendmsg_locked``tcp_write_xmit` → …
* `__x64_sys_recvfrom``tcp_recvmsg` → …
2. My userspace frames existed, but they were thin compared to the kernel towers.
That means:
* Im not burning CPU on complicated Rust logic.
* Im paying overhead on the boundary: syscalls, TCP stack, copies.
3. In the dwarf flamegraph, the *userspace* frames pointed to my forwarding implementation:
* the code path that ultimately calls read/write repeatedly.
> **Conclusion:** This is not “async is slow” in general. This is “my relay loop is forcing too many small kernel transitions.”
## 6. The Suspect: my forwarding code
Here was the original TCP relay:
```rust
// Use smol's copy function to forward data in both directions
let client_to_server = io::copy(client_stream.clone(), server_stream.clone());
let server_to_client = io::copy(server_stream, client_stream);
futures_lite::future::try_zip(client_to_server, server_to_client).await?;
```
> **Inner Prosecutor:** “*Objection!* That looks perfectly reasonable.”
>
> **Me:** “Yes. Thats why its dangerous.”
### Why this can be slow under high throughput
Generic `io::copy` helpers often use a relatively small internal buffer (commonly ~8KiB), plus abstraction layers that can increase:
* syscall frequency
* readiness polling
* per-chunk overhead
Small buffers arent “wrong”. Theyre memory-friendly. But for a forwarder pushing tens of Gbit/s, **syscalls per byte** becomes the real limiter.
---
## 7. The Fix: a manual `pump()` loop (and a buffer size sweep)
I replaced `io::copy` with a manual relay loop:
* allocate a buffer once per direction
* read into it
* write it out
* on EOF, propagate half-close with `shutdown(Write)`
Code (core idea):
```rust
async fn pump(mut r: TcpStream, mut w: TcpStream, buf_sz: usize) -> io::Result<u64> {
let mut buf = vec![0u8; buf_sz];
let mut total = 0u64;
loop {
let n = r.read(&mut buf).await?;
if n == 0 {
let _ = w.shutdown(std::net::Shutdown::Write);
break;
}
w.write_all(&buf[..n]).await?;
total += n as u64;
}
Ok(total)
}
```
And run both directions:
```rust
let c2s = pump(client_stream.clone(), server_stream.clone(), BUF);
let s2c = pump(server_stream, client_stream, BUF);
try_zip(c2s, s2c).await?;
```
---
> **Inner Prosecutor:** “You changed one helper call into a loop. Thats your miracle?”
>
> **Me:** “Not the loop. The *bytes per syscall*.”
---
## 8. Verification: numbers dont lie
Same machine, same namespaces/veth, same `iperf3 -P 8`.
### Baseline (generic copy, ~8KiB internal buffer)
Throughput:
```text
17.8 Gbit/s
```
### Pump + 16KiB buffer
Throughput:
```text
28.6 Gbit/s
```
`strace -c` showed `sendto/recvfrom` call count dropped:
```text
% time seconds usecs/call calls errors syscall
------ ----------- ----------- --------- --------- ----------------
57.80 14.590016 442121 33 epoll_wait
28.84 7.279883 4 1771146 sendto
13.33 3.363882 1 1771212 48 recvfrom
0.02 0.003843 61 62 44 futex
0.01 0.001947 12 159 epoll_ctl
...
------ ----------- ----------- --------- --------- ----------------
100.00 25.242897 7 3542787 143 total
```
### Pump + 64KiB buffer
Throughput:
```text
54.1 Gbit/s (best observed)
```
`perf stat` output:
```text
Performance counter stats for process id '893123':
120,859,810,675 cpu_atom/cycles/ (0.15%)
134,735,934,329 cpu_core/cycles/ (99.85%)
79,946,979,880 cpu_atom/instructions/ # 0.66 insn per cycle (0.15%)
127,036,644,759 cpu_core/instructions/ # 0.94 insn per cycle (99.85%)
24,713,474 cpu_atom/cache-misses/ (0.15%)
9,604,449 cpu_core/cache-misses/ (99.85%)
15,584,074,530 cpu_atom/branches/ (0.15%)
24,796,180,117 cpu_core/branches/ (99.85%)
175,778,825 cpu_atom/branch-misses/ # 1.13% of all branches (0.15%)
135,067,353 cpu_core/branch-misses/ # 0.54% of all branches (99.85%)
1,519 context-switches
50 cpu-migrations
33.006529572 seconds time elapsed
```
`strace -c` output:
```text
% time seconds usecs/call calls errors syscall
------ ----------- ----------- --------- --------- ----------------
54.56 18.079500 463576 39 epoll_wait
27.91 9.249443 7 1294854 2 sendto
17.49 5.796927 4 1294919 51 recvfrom
...
------ ----------- ----------- --------- --------- ----------------
100.00 33.135377 12 2590253 158 total
```
---
## 9. “Wait — why is `epoll_wait` taking most syscall time?”
> **Inner Prosecutor:** “*Objection!* Your table says `epoll_wait` dominates time. So epoll is the bottleneck!”
>
> **Me:** “Nope. Thats a common misread.”
`strace -c` counts **time spent inside syscalls**, including time spent **blocked**.
In async runtimes, its normal for one thread to sit in `epoll_wait(timeout=...)` while other threads do actual send/recv work. That blocking time is charged to `epoll_wait`, but its not “overhead” — its *waiting*.
The real signal is still:
* `sendto/recvfrom` call counts (millions)
* average microseconds per call
* and whether call count drops when buffer size increases
Thats the syscall-per-byte story.
---
## 10. So why did 64KiB cause such a huge jump?
Two reasons:
### 1) Syscall wall is nonlinear
Throughput is roughly:
**Throughput ≈ bytes_per_syscall_pair × syscall_pairs_per_second**
If syscall rate is the limiter, increasing bytes per syscall can push you past a threshold where:
* socket buffers stay fuller
* TCP windows are better utilized
* per-stream pacing is smoother
* concurrency (`-P 8`) stops fighting overhead and starts working in your favor
Once you cross that threshold, throughput can jump until the *next* ceiling (kernel TCP work, memory bandwidth, or iperf itself).
### 2) Less “per-chunk” overhead in userspace
A small-buffer copy loop means more iterations, more polls, more bookkeeping.
A bigger buffer means:
* fewer loop iterations per GB moved
* fewer wakeups/polls
* fewer syscall transitions per GB
Your `strace` call counts dropped significantly between 16KiB and 64KiB, and throughput nearly doubled.
---
## 11. Trade-offs: buffer size is not free
> **Inner Prosecutor:** “*Hold it!* Bigger buffers mean wasted memory.”
>
> **Me:** “Correct.”
A forwarder allocates **two buffers per connection** (one per direction).
So for 64KiB:
* ~128KiB per connection (just for relay buffers)
* plus runtime + socket buffers
Thats fine for “few heavy streams”, but it matters if you handle thousands of concurrent connections.
In practice, the right move is:
* choose a good default (64KiB is common)
* make it configurable
* consider buffer pooling if connection churn is heavy
---
## 12. Closing statement
This was a good reminder that performance work is not guessing — its a dialogue with the system:
1. Describe the situation
2. Ask sharp questions
3. Use tools to confirm
4. Explain the results using low-level knowledge
5. Make one change
6. Re-measure
And the funniest part: the “clean” one-liner `io::copy` was correct, but its defaults were hiding a performance policy I didnt want.
> **Inner Prosecutor:** “Case closed?”
>
> **Me:** “For now. Next case: buffer pooling, socket buffer tuning, and maybe a Linux-only `splice(2)` fast path — carefully, behind a safe wrapper.”
---
title: Ace Profiling Attorney - The Case of the Missing Gbits
categories: [Programming, Profiling]
tags: [Rust, kernel, networking]
---
> **Disclaimer:** This is not a language-war post. No “X vs Y”.
> This is a profiling detective story about my Rust TCP forwarder [`oi`](https://github.com/DaZuo0122/oxidinetd).
---
## 0) Prologue — The Courthouse Lobby
> **Me:** I wrote a Rust TCP port forwarder. It works. It forwards.
>
> **Inner Prosecutor (Phoenix voice):** *Hold it!* “Works” is not a metric. How fast?
>
> **Me:** Not fast enough under load.
>
> **Inner Prosecutor:** *Objection!* “Not fast enough” is an emotion. Bring evidence.
>
> **Me:** Fine. Ill bring **perf**, **strace**, and a **flamegraph**.
>
> **Inner Prosecutor:** Good. This court accepts only facts.
## 1) The Crime Scene — Setup & Reproduction
**Me:** Single machine, Debian 13. No WAN noise, no tunnel bottlenecks.
**Inner Prosecutor:** *Hold it!* If its “single machine”, how do you avoid loopback cheating?
**Me:** Network namespaces + veth. Local, repeatable, closer to real networking.
### Environment
- Debian 13
- Kernel: `6.12.48+deb13-amd64`
- Runtime: `smol`
- Test topology: `ns_client → oi (root ns) → ns_server` via veth
### Reproduction commands
**Exhibit A: Start backend server in `ns_server`**
```bash
sudo ip netns exec ns_server iperf3 -s -p 9001
````
**Exhibit B: Run client in `ns_client` through forwarder**
```bash
sudo ip netns exec ns_client iperf3 -c 10.0.1.1 -p 9000 -t 30 -P 8
```
**Inner Prosecutor:** *Hold it!* Why `-P 8`?
**Me:** Because a forwarder can look fine in `-P 1` and fall apart when syscall pressure scales.
**Inner Prosecutor:** …Acceptable.
---
## 2) The Suspects — What Could Be Limiting Throughput?
**Me:** Four suspects.
1. **CPU bound** (pure compute wall)
2. **Kernel TCP stack bound** (send/recv path, skb, softirq, netfilter/conntrack)
3. **Syscall-rate wall** (too many `sendto/recvfrom` per byte)
4. **Runtime scheduling / contention** (wake storms, locks, futex)
**Inner Prosecutor:** *Objection!* Thats too broad. Narrow it down.
**Me:** Thats what the tools are for.
---
## 3) Evidence #1 — `perf stat` (The Macro View)
**Me:** First I ask: are we burning CPU, thrashing schedulers, or stalling on memory?
**Command:**
```bash
sudo perf stat -p $(pidof oi) -e \
cycles,instructions,cache-misses,branches,branch-misses,context-switches,cpu-migrations \
-- sleep 33
```
**What Im looking for:**
* Huge `context-switches` → runtime thrash / lock contention
* Huge `cpu-migrations` → unstable scheduling
* Very low IPC + huge cache misses → memory stalls
* Otherwise: likely syscall/kernel path
Output:
```text
Performance counter stats for process id '209785':
113,810,599,893 cpu_atom/cycles/ (0.11%)
164,681,878,450 cpu_core/cycles/ (99.89%)
102,575,167,734 cpu_atom/instructions/ # 0.90 insn per cycle (0.11%)
237,094,207,911 cpu_core/instructions/ # 1.44 insn per cycle (99.89%)
33,093,338 cpu_atom/cache-misses/ (0.11%)
5,381,441 cpu_core/cache-misses/ (99.89%)
20,012,975,873 cpu_atom/branches/ (0.11%)
46,120,077,111 cpu_core/branches/ (99.89%)
211,767,555 cpu_atom/branch-misses/ # 1.06% of all branches (0.11%)
245,969,685 cpu_core/branch-misses/ # 0.53% of all branches (99.89%)
1,686 context-switches
150 cpu-migrations
33.004363800 seconds time elapsed
```
**Low context switching**:
- context-switches: 1,686 over ~33s → ~51 switches/sec
- cpu-migrations: 150 over ~33s → ~4.5/s → very stable CPU placement
**CPU is working hard**:
- 237,094,207,911 cpu_core instructions
- IPC: 1.44 (instructions per cycle) → not lock-bound or stalling badly
**Clean cache, branch metrics**:
- cache-misses: ~3.1M (tiny compared to the instruction count)
- branch-misses: 0.62%
**Inner Prosecutor:** *Hold it!* You didnt show the numbers.
**Me:** Patience. The next exhibit makes the culprit confess.
---
## 4) Evidence #2 — `strace -c` (The Confession: Syscall Composition)
**Me:** Next: “What syscalls are we paying for?”
**Command:**
```bash
sudo timeout 30s strace -c -f -p $(pidof oi)
```
**What I expect if this is a forwarding wall:**
* `sendto` and `recvfrom` dominate calls
* call counts in the millions
Output (simplified):
```text
sendto 2,190,751 calls 4.146799s (57.6%)
recvfrom 2,190,763 calls 3.052340s (42.4%)
total syscall time: 7.200789s
```
(A) **100% syscall/copy dominated:**
- Almost all traced time is inside:
- sendto() (TCP send)
- recvfrom() (TCP recv)
(B) **syscall rate is massive**
- Total send+recv calls:
- ~4,381,500 syscalls in ~32s
- → ~137k `sendto` per sec + ~137k `recvfrom` per sec
- → ~274k syscalls/sec total
**Inner Prosecutor:** *Objection!* Syscalls alone dont prove the bottleneck.
**Me:** True. So I brought a witness.
---
## 5) Evidence #3 — FlameGraph (The Witness)
**Me:** The flamegraph doesnt lie. It testifies where cycles go.
**Commands:**
```bash
sudo perf record -F 199 --call-graph dwarf,16384 -p $(pidof oi) -- sleep 30
sudo perf script | stackcollapse-perf.pl | flamegraph.pl > oi.svg
```
**What the flamegraph showed (described, not embedded):**
* The widest towers were kernel TCP send/recv paths:
* `__x64_sys_sendto``tcp_sendmsg_locked``tcp_write_xmit` → ...
* `__x64_sys_recvfrom``tcp_recvmsg` → ...
* My userspace frames existed, but were comparatively thin.
* The call chain still pointed into my forwarding implementation.
**Inner Prosecutor:** *Hold it!* So youre saying… the kernel is doing the heavy lifting?
**Me:** Exactly. Which means my job is to **stop annoying the kernel** with too many tiny operations.
---
## 6) The Real Culprit — A “Perfectly Reasonable” Copy Loop
**Me:** Heres the original relay code. Looks clean, right?
```rust
let client_to_server = io::copy(client_stream.clone(), server_stream.clone());
let server_to_client = io::copy(server_stream, client_stream);
futures_lite::future::try_zip(client_to_server, server_to_client).await?;
```
**Inner Prosecutor:** *Objection!* This is idiomatic and correct.
**Me:** Yes. Thats why its dangerous.
**Key detail:** `futures_lite::io::copy` uses a small internal buffer (~8KiB in practice).
Small buffer → more iterations → more syscalls → more overhead.
If a forwarder is syscall-rate bound, this becomes a ceiling.
---
## 7) The First Breakthrough — Replace `io::copy` with `pump()`
**Me:** I wrote a manual pump loop:
* allocate a buffer once
* `read()` into it
* `write_all()` out
* on EOF: `shutdown(Write)` to propagate half-close
```rust
async fn pump(mut r: TcpStream, mut w: TcpStream, buf_sz: usize) -> io::Result<u64> {
let mut buf = vec![0u8; buf_sz];
let mut total = 0u64;
loop {
let n = r.read(&mut buf).await?;
if n == 0 {
let _ = w.shutdown(std::net::Shutdown::Write);
break;
}
w.write_all(&buf[..n]).await?;
total += n as u64;
}
Ok(total)
}
```
Run both directions:
```rust
let c2s = pump(client_stream.clone(), server_stream.clone(), BUF);
let s2c = pump(server_stream, client_stream, BUF);
try_zip(c2s, s2c).await?;
```
**Inner Prosecutor:** *Hold it!* Thats just a loop. How does that win?
**Me:** Not the loop. The **bytes per syscall**.
---
### 8) Exhibit C — The Numbers (8KiB → 16KiB → 64KiB)
### Baseline: ~8KiB (generic copy helper)
Throughput:
```text
17.8 Gbit/s
```
**Inner Prosecutor:** *Objection!* Thats your “crime scene” number?
**Me:** Yes. Now watch what happens when the kernel stops getting spammed.
### Pump + 16KiB buffer
Throughput:
```text
28.6 Gbit/s
```
`strace -c` showed `sendto/recvfrom` call count dropped:
```text
% time seconds usecs/call calls errors syscall
------ ----------- ----------- --------- --------- ----------------
57.80 14.590016 442121 33 epoll_wait
28.84 7.279883 4 1771146 sendto
13.33 3.363882 1 1771212 48 recvfrom
0.02 0.003843 61 62 44 futex
0.01 0.001947 12 159 epoll_ctl
...
------ ----------- ----------- --------- --------- ----------------
100.00 25.242897 7 3542787 143 total
```
**Inner Prosecutor:** *Hold it!* Thats already big. But you claim theres more?
**Me:** Oh, theres more.
### Pump + 64KiB buffer
Throughput:
```text
54.1 Gbit/s (best observed)
```
`perf stat` output:
```text
Performance counter stats for process id '893123':
120,859,810,675 cpu_atom/cycles/ (0.15%)
134,735,934,329 cpu_core/cycles/ (99.85%)
79,946,979,880 cpu_atom/instructions/ # 0.66 insn per cycle (0.15%)
127,036,644,759 cpu_core/instructions/ # 0.94 insn per cycle (99.85%)
24,713,474 cpu_atom/cache-misses/ (0.15%)
9,604,449 cpu_core/cache-misses/ (99.85%)
15,584,074,530 cpu_atom/branches/ (0.15%)
24,796,180,117 cpu_core/branches/ (99.85%)
175,778,825 cpu_atom/branch-misses/ # 1.13% of all branches (0.15%)
135,067,353 cpu_core/branch-misses/ # 0.54% of all branches (99.85%)
1,519 context-switches
50 cpu-migrations
33.006529572 seconds time elapsed
```
`strace -c` output:
```text
% time seconds usecs/call calls errors syscall
------ ----------- ----------- --------- --------- ----------------
54.56 18.079500 463576 39 epoll_wait
27.91 9.249443 7 1294854 2 sendto
17.49 5.796927 4 1294919 51 recvfrom
...
------ ----------- ----------- --------- --------- ----------------
100.00 33.135377 12 2590253 158 total
```
**Inner Prosecutor:** *OBJECTION!* `epoll_wait` is eating the time. Thats the bottleneck!
**Me:** Nice try. Thats a classic trap.
---
## 9) Cross-Examination — The `epoll_wait` Trap
**Me:** `strace -c` measures time spent *inside syscalls*, including time spent **blocked**.
In async runtimes:
* One thread can sit in `epoll_wait(timeout=...)`
* Other threads do `sendto/recvfrom`
* `strace` charges the blocking time to `epoll_wait`
So `epoll_wait` dominating **does not** mean “epoll is slow”.
It often means “one thread is waiting while others work”.
**What matters here:**
* `sendto` / `recvfrom` call counts
* and how they change with buffer size
---
## 10) Final Explanation — Why 64KiB Causes a “Nonlinear” Jump
**Inner Prosecutor:** *Hold it!* You only reduced syscall calls by ~some percent. How do you nearly triple throughput?
**Me:** Because syscall walls are **nonlinear**.
A forwarders throughput is approximately:
> **Throughput ≈ bytes_per_syscall_pair × syscall_pairs_per_second**
If youre syscall-rate limited, increasing `bytes_per_syscall_pair` pushes you past a threshold where:
* socket buffers stay fuller
* the TCP window is better utilized
* each stream spends less time in per-chunk bookkeeping
* concurrency (`-P 8`) stops fighting overhead and starts helping
Once you cross that threshold, throughput can jump until the next ceiling (kernel TCP, memory bandwidth, iperf itself).
Thats why a “small” change can create a big effect.
---
## 11. Trade-offs: buffer size is not free
**Inner Prosecutor:** *Objection!* Bigger buffers waste memory!
**Me:** Sustained.
A forwarder allocates **two buffers per connection** (one per direction).
So for 64KiB:
* ~128KiB per connection (just for relay buffers)
* plus runtime + socket buffers
Thats fine for “few heavy streams”, but it matters if you handle thousands of concurrent connections.
In practice, the right move is:
* choose a good default (64KiB is common)
* make it configurable
* consider buffer pooling if connection churn is heavy
---
## Epilogue — Case Closed (for now)
**Inner Prosecutor:** So the culprit was…
**Me:** A perfectly reasonable helper with a default buffer size I didnt question.
**Inner Prosecutor:** And the lesson?
**Me:** Dont guess. Ask sharp questions. Use the tools. Let the system testify.
> **Verdict:** Guilty of “too many syscalls per byte.”
>
> **Sentence:** 64KiB buffers and a better relay loop.
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## Ending
This was a good reminder that performance work is not guessing — its a dialogue with the system:
1. Describe the situation
2. Ask sharp questions
3. Use tools to confirm
4. Explain the results using low-level knowledge
5. Make one change
6. Re-measure
And the funniest part: the “clean” one-liner `io::copy` was correct, but its defaults were hiding a performance policy I didnt want.
> **Inner Prosecutor:** “Case closed?”
>
> **Me:** “For now. Next case: buffer pooling, socket buffer tuning, and maybe a Linux-only `splice(2)` fast path — carefully, behind a safe wrapper.”
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