Daily update on 20260307-020120 by Nitload Youmu. Additional Message : None

Signed-off-by: Nitload <YoumuLiu_NSI@whv0t.onmicrosoft.com>
This commit is contained in:
Nitload
2026-03-07 02:01:20 +08:00
parent 405f895e29
commit 64360b63a1
4 changed files with 475 additions and 192 deletions
+403 -151
View File
@@ -29,41 +29,127 @@ using BenchmarkDotNet.Attributes;
using StgSharp.Collections; using StgSharp.Collections;
using System; using System;
using System.Collections.Generic; using System.Collections.Generic;
using System.Runtime.CompilerServices;
namespace StgSharp.Benchmark namespace StgSharp.Benchmark
{ {
/// <summary> /// <summary>
/// Benchmark comparing SwissTable (SSE2 SIMD probing, zero-GC, native memory) against <see /// Benchmark comparing SwissTable against <see cref="Dictionary{TKey, TValue}" />
/// cref="Dictionary{TKey, TValue}" /> for the L4 cache address mapping workload: concentrated /// under realistic L4 software cache address-mapping workloads.
/// small-key insert/lookup/remove cycles. <para> SwissTable.Create() performs a 1 MB memset /// <para>
/// (65536 × 16 control bytes), which is separated into IterationSetup to avoid polluting /// L4 scenario characteristics:
/// insert timings.</para> /// - Keys are HLSF/malloc pointer addresses (large, 1024-byte aligned)
/// - Access pattern is Zipfian-skewed (20% hot cache lines receive 80% of lookups)
/// - Steady state: high hit-rate lookups dominate, with rare evict+refill on miss
/// - Working set: 512–4096 active cache line mappings
/// </para>
/// </summary> /// </summary>
[MemoryDiagnoser] [MemoryDiagnoser]
public class SwissTableBench public class SwissTableBench
{ {
private const int LookupCount = 4096; /// <summary> L4 cache line size in bytes (per L4_design.md). </summary>
private const int CacheLineSize = 1024;
private nint[] _lookupKeys = null!; /// <summary> Simulated heap base address for pointer-like keys. </summary>
private const long HeapBase = 0x7FFF_0000_0000L;
// ── Pre-generated key arrays ── /// <summary> Number of lookup operations per Lookup benchmark call. </summary>
private const int LookupIterations = 8192;
private nint[] _preloadedKeys = null!; /// <summary>
/// Number of steady-state operations per call.
/// Each op is either a lookup (hit) or an evict+insert+lookup (miss).
/// </summary>
private const int SteadyStateOps = 4096;
/// <summary> Fraction of steady-state ops that are cache misses. </summary>
private const double MissRate = 0.05;
// ── Pre-generated key arrays (pointer-like, 1024-byte aligned) ──
/// <summary> Keys for initial table fill (simulates cached addresses). </summary>
private nint[] _residentKeys = null!;
/// <summary> Additional keys not in the table, for triggering misses. </summary>
private nint[] _externalKeys = null!;
/// <summary> Zipfian-skewed lookup sequence (hot 20% accessed 80% of time). </summary>
private nint[] _zipfianLookups = null!;
/// <summary> Uniform random lookup sequence (baseline comparison). </summary>
private nint[] _uniformLookups = null!;
/// <summary>
/// Pre-built steady-state operation script.
/// Each entry: positive index → lookup _residentKeys[idx],
/// negative value → cache miss trigger (evict + insert from _externalKeys).
/// </summary>
private int[] _steadyStateScript = null!;
/// <summary> Indices into _residentKeys for eviction targets (cold entries, tail region). </summary>
private int[] _evictOrder = null!;
// ── Pre-filled lookup targets ──
private SwissTable _swissLookup = null!;
private Dictionary<nint, nint> _dictLookup = null!; private Dictionary<nint, nint> _dictLookup = null!;
private Dictionary<nint, nint> _freshDict = null!;
// ── Fresh instances for insert/mixed (rebuilt each iteration) ── // ── Fresh instances for insert/mixed (rebuilt each iteration) ──
private SwissTable _freshSwiss = null!; private SwissTable _freshSwiss = null!;
private Dictionary<nint, nint> _freshDict = null!;
// ── Lookup targets (pre-filled in GlobalSetup) ── /// <summary>
/// Active cache line count. Matches L4 capacity range:
private SwissTable _swissLookup = null!; /// 5 MB / 1024B ≈ 5120, 10 MB / 1024B ≈ 10240.
/// 512 and 1024 test low-occupancy; 4096 tests near-capacity.
[Params(500, 2000, 5000)] /// </summary>
[Params(512, 1024, 4096)]
public int KeyCount; public int KeyCount;
// ════════════════════════════════════════════════════════════
// Setup / Teardown
// ════════════════════════════════════════════════════════════
[GlobalSetup]
public void Setup()
{
Random rng = new Random(42);
// ── Generate pointer-like keys (HeapBase + random_offset * 1024) ──
_residentKeys = GeneratePointerKeys(KeyCount, rng);
_externalKeys = GeneratePointerKeys(KeyCount, rng); // disjoint set for miss simulation
// ── Build lookup sequences ──
_zipfianLookups = GenerateZipfianLookups(_residentKeys, LookupIterations, rng);
_uniformLookups = GenerateUniformLookups(_residentKeys, LookupIterations, rng);
// ── Build steady-state operation script ──
_steadyStateScript = GenerateSteadyStateScript(KeyCount, SteadyStateOps, MissRate, rng);
// ── Build eviction order (cold tail entries first) ──
_evictOrder = new int[KeyCount];
for (int i = 0; i < KeyCount; i++)
{
_evictOrder[i] = i;
}
// Shuffle so eviction isn't just sequential
Shuffle(_evictOrder, rng);
// ── Pre-fill lookup tables ──
_swissLookup = SwissTable.Create();
_dictLookup = new Dictionary<nint, nint>(KeyCount);
for (int i = 0; i < KeyCount; i++)
{
nint key = _residentKeys[i];
nint val = key ^ unchecked((nint)0xDEAD_BEEF); // simulated cache pointer
_swissLookup.TryAddOrSet(key, val, out _);
_dictLookup[key] = val;
}
}
[GlobalCleanup] [GlobalCleanup]
public void Cleanup() public void Cleanup()
{ {
@@ -71,119 +157,114 @@ namespace StgSharp.Benchmark
_dictLookup.TrimExcess(); _dictLookup.TrimExcess();
} }
// ══════════════════════════════════════
// Insert: pure write throughput
// Empty table → fill N keys
// Create() cost excluded via IterationSetup
// ══════════════════════════════════════
[Benchmark]
public void Dictionary_Insert()
{
Dictionary<nint, nint> dict = _freshDict;
nint[] keys = _preloadedKeys;
for (int i = 0; i < keys.Length; i++) {
dict[keys[i]] = keys[i] * 2;
}
}
// ══════════════════════════════════════
// Lookup: pure read throughput
// Pre-filled table, random key access
// ══════════════════════════════════════
[Benchmark(Baseline = true)]
public nint Dictionary_Lookup()
{
nint sum = 0;
nint[] keys = _lookupKeys;
Dictionary<nint, nint> dict = _dictLookup;
for (int i = 0; i < keys.Length; i++)
{
if (dict.TryGetValue(keys[i], out nint value)) {
sum += value;
}
}
return sum;
}
// ══════════════════════════════════════
// Mixed: insert all → lookup half → remove half → lookup all
// Simulates L4 cache lifecycle:
// load working set → compute → evict → recompute
// ══════════════════════════════════════
[Benchmark]
public nint Dictionary_Mixed()
{
Dictionary<nint, nint> dict = _freshDict;
nint[] keys = _preloadedKeys;
nint sum = 0;
// insert all
for (int i = 0; i < keys.Length; i++)
{
dict[keys[i]] = keys[i] * 2;
}
// lookup first half
for (int i = 0; i < keys.Length / 2; i++)
{
if (dict.TryGetValue(keys[i], out nint value)) {
sum += value;
}
}
// remove first half (eviction)
for (int i = 0; i < keys.Length / 2; i++)
{
dict.Remove(keys[i]);
}
// lookup all (half hit, half miss)
for (int i = 0; i < keys.Length; i++)
{
if (dict.TryGetValue(keys[i], out nint value)) {
sum += value;
}
}
return sum;
}
[IterationSetup(Targets = [ [IterationSetup(Targets = [
nameof(SwissTable_Insert), nameof(SwissTable_Insert),
nameof(SwissTable_Mixed), nameof(SwissTable_SteadyState),
nameof(Dictionary_Insert), nameof(Dictionary_Insert),
nameof(Dictionary_Mixed) nameof(Dictionary_SteadyState)
])] ])]
public void IterationSetup() public void IterationSetup()
{ {
_freshSwiss = SwissTable.Create(); _freshSwiss = SwissTable.Create();
_freshDict = new Dictionary<nint, nint>(KeyCount); _freshDict = new Dictionary<nint, nint>(KeyCount);
}
// ── Setup / Teardown ──
[GlobalSetup]
public void Setup()
{
_preloadedKeys = new nint[KeyCount];
_lookupKeys = new nint[LookupCount];
_swissLookup = SwissTable.Create();
_dictLookup = new Dictionary<nint, nint>(KeyCount);
// Pre-fill for steady-state benchmarks
for (int i = 0; i < KeyCount; i++) for (int i = 0; i < KeyCount; i++)
{ {
_preloadedKeys[i] = (nint)i; nint key = _residentKeys[i];
_swissLookup.TryAddOrSet((nint)i, (nint)(i * 2), out _); nint val = key ^ unchecked((nint)0xDEAD_BEEF);
_dictLookup[(nint)i] = (nint)(i * 2); _freshSwiss.TryAddOrSet(key, val, out _);
_freshDict[key] = val;
} }
}
Random rng = new Random(42); // ════════════════════════════════════════════════════════════
for (int i = 0; i < LookupCount; i++) { // Lookup — Zipfian (L4 hot path, skewed access)
_lookupKeys[i] = (nint)rng.Next(0, KeyCount); // 20% of cache lines receive 80% of accesses.
// This is the most representative L4 benchmark.
// ════════════════════════════════════════════════════════════
[Benchmark(Baseline = true)]
public nint Dictionary_Lookup_Zipfian()
{
nint sum = 0;
nint[] keys = _zipfianLookups;
Dictionary<nint, nint> dict = _dictLookup;
for (int i = 0; i < keys.Length; i++)
{
if (dict.TryGetValue(keys[i], out nint value))
{
sum += value;
}
}
return sum;
}
[Benchmark]
public nint SwissTable_Lookup_Zipfian()
{
nint sum = 0;
nint[] keys = _zipfianLookups;
SwissTable swiss = _swissLookup;
for (int i = 0; i < keys.Length; i++)
{
if (swiss.TryGet(keys[i], out nint value))
{
sum += value;
}
}
return sum;
}
// ════════════════════════════════════════════════════════════
// Lookup — Uniform (baseline comparison)
// ════════════════════════════════════════════════════════════
[Benchmark]
public nint Dictionary_Lookup_Uniform()
{
nint sum = 0;
nint[] keys = _uniformLookups;
Dictionary<nint, nint> dict = _dictLookup;
for (int i = 0; i < keys.Length; i++)
{
if (dict.TryGetValue(keys[i], out nint value))
{
sum += value;
}
}
return sum;
}
[Benchmark]
public nint SwissTable_Lookup_Uniform()
{
nint sum = 0;
nint[] keys = _uniformLookups;
SwissTable swiss = _swissLookup;
for (int i = 0; i < keys.Length; i++)
{
if (swiss.TryGet(keys[i], out nint value))
{
sum += value;
}
}
return sum;
}
// ════════════════════════════════════════════════════════════
// Insert — bulk fill with scattered pointer addresses
// Simulates L4 initial cache warm-up phase.
// ════════════════════════════════════════════════════════════
[Benchmark]
public void Dictionary_Insert()
{
Dictionary<nint, nint> dict = _freshDict;
nint[] keys = _residentKeys;
for (int i = 0; i < keys.Length; i++)
{
dict[keys[i]] = keys[i] ^ unchecked((nint)0xDEAD_BEEF);
} }
} }
@@ -191,64 +272,235 @@ namespace StgSharp.Benchmark
public void SwissTable_Insert() public void SwissTable_Insert()
{ {
SwissTable swiss = _freshSwiss; SwissTable swiss = _freshSwiss;
nint[] keys = _preloadedKeys; nint[] keys = _residentKeys;
for (int i = 0; i < keys.Length; i++) { for (int i = 0; i < keys.Length; i++)
swiss.TryAddOrSet(keys[i], keys[i] * 2, out _); {
swiss.TryAddOrSet(keys[i], keys[i] ^ unchecked((nint)0xDEAD_BEEF), out _);
} }
} }
// ════════════════════════════════════════════════════════════
// SteadyState — the KEY L4 benchmark
// Pre-filled table at capacity, then 4096 operations:
// ~95% are lookups (cache hits)
// ~5% are miss → evict cold entry → insert new entry → lookup new
// This directly simulates L4's main runtime loop.
// ════════════════════════════════════════════════════════════
[Benchmark] [Benchmark]
public nint SwissTable_Lookup() public nint Dictionary_SteadyState()
{ {
nint sum = 0; nint sum = 0;
nint[] keys = _lookupKeys; Dictionary<nint, nint> dict = _freshDict;
SwissTable swiss = _swissLookup; nint[] resident = _residentKeys;
for (int i = 0; i < keys.Length; i++) nint[] external = _externalKeys;
int[] script = _steadyStateScript;
int[] evict = _evictOrder;
int evictCursor = 0;
int externalCursor = 0;
for (int i = 0; i < script.Length; i++)
{ {
if (swiss.TryGet(keys[i], out nint value)) { int op = script[i];
sum += value; if (op >= 0)
{
// Cache hit: lookup existing entry
if (dict.TryGetValue(resident[op], out nint value))
{
sum += value;
}
}
else
{
// Cache miss: evict a cold entry, insert a new one, then lookup
int evictIdx = evict[evictCursor % evict.Length];
evictCursor++;
dict.Remove(resident[evictIdx]);
int extIdx = externalCursor % external.Length;
externalCursor++;
nint newKey = external[extIdx];
nint newVal = newKey ^ unchecked((nint)0xDEAD_BEEF);
dict[newKey] = newVal;
if (dict.TryGetValue(newKey, out nint v))
{
sum += v;
}
} }
} }
return sum; return sum;
} }
[Benchmark] [Benchmark]
public nint SwissTable_Mixed() public nint SwissTable_SteadyState()
{ {
nint sum = 0;
SwissTable swiss = _freshSwiss; SwissTable swiss = _freshSwiss;
nint[] keys = _preloadedKeys; nint[] resident = _residentKeys;
nint sum = 0; nint[] external = _externalKeys;
int[] script = _steadyStateScript;
int[] evict = _evictOrder;
int evictCursor = 0;
int externalCursor = 0;
// insert all for (int i = 0; i < script.Length; i++)
for (int i = 0; i < keys.Length; i++)
{ {
swiss.TryAddOrSet(keys[i], keys[i] * 2, out _); int op = script[i];
} if (op >= 0)
{
// Cache hit: lookup existing entry
if (swiss.TryGet(resident[op], out nint value))
{
sum += value;
}
}
else
{
// Cache miss: evict a cold entry, insert a new one, then lookup
int evictIdx = evict[evictCursor % evict.Length];
evictCursor++;
swiss.TryRemove(resident[evictIdx], out _);
// lookup first half int extIdx = externalCursor % external.Length;
for (int i = 0; i < keys.Length / 2; i++) externalCursor++;
{ nint newKey = external[extIdx];
if (swiss.TryGet(keys[i], out nint value)) { nint newVal = newKey ^ unchecked((nint)0xDEAD_BEEF);
sum += value; swiss.TryAddOrSet(newKey, newVal, out _);
if (swiss.TryGet(newKey, out nint v))
{
sum += v;
}
} }
} }
// remove first half (eviction)
for (int i = 0; i < keys.Length / 2; i++)
{
swiss.TryRemove(keys[i], out _);
}
// lookup all (half hit, half miss)
for (int i = 0; i < keys.Length; i++)
{
if (swiss.TryGet(keys[i], out nint value)) {
sum += value;
}
}
return sum; return sum;
} }
// ════════════════════════════════════════════════════════════
// Data generation helpers
// ════════════════════════════════════════════════════════════
/// <summary>
/// Generate <paramref name="count"/> unique pointer-like keys.
/// Each key = HeapBase + randomOffset * CacheLineSize,
/// simulating HLSF-allocated 1024-byte aligned addresses
/// scattered across a ~1 GB virtual address range.
/// </summary>
private static nint[] GeneratePointerKeys(
int count,
Random rng
)
{
nint[] keys = new nint[count];
HashSet<long> used = new HashSet<long>(count);
for (int i = 0; i < count; i++)
{
long offset;
do
{
// Random offset within ~1M cache lines (1 GB range)
offset = (long)rng.Next(0, 1 << 20) * CacheLineSize;
} while (!used.Add(offset));
keys[i] = (nint)(HeapBase + offset);
}
return keys;
}
/// <summary>
/// Generate Zipfian-skewed lookup sequence:
/// 80% of accesses hit the hottest 20% of keys (sorted by index as "hotness proxy"),
/// 20% of accesses hit the remaining 80%.
/// This models matrix computation where a small panel working set is reused heavily.
/// </summary>
private static nint[] GenerateZipfianLookups(
nint[] sourceKeys,
int count,
Random rng
)
{
int hotSetSize = Math.Max(1, sourceKeys.Length / 5);
nint[] lookups = new nint[count];
for (int i = 0; i < count; i++)
{
if (rng.NextDouble() < 0.8)
{
lookups[i] = sourceKeys[rng.Next(0, hotSetSize)];
}
else
{
lookups[i] = sourceKeys[rng.Next(hotSetSize, sourceKeys.Length)];
}
}
return lookups;
}
/// <summary>
/// Generate uniform random lookup sequence (baseline for comparison with Zipfian).
/// </summary>
private static nint[] GenerateUniformLookups(
nint[] sourceKeys,
int count,
Random rng
)
{
nint[] lookups = new nint[count];
for (int i = 0; i < count; i++)
{
lookups[i] = sourceKeys[rng.Next(0, sourceKeys.Length)];
}
return lookups;
}
/// <summary>
/// Generate a steady-state operation script.
/// Each entry: non-negative value = index into _residentKeys (lookup/hit),
/// negative value (-1) = cache miss trigger (evict → insert → lookup).
/// Lookup indices are Zipfian-skewed.
/// </summary>
private static int[] GenerateSteadyStateScript(
int keyCount,
int opCount,
double missRate,
Random rng
)
{
int hotSetSize = Math.Max(1, keyCount / 5);
int[] script = new int[opCount];
for (int i = 0; i < opCount; i++)
{
if (rng.NextDouble() < missRate)
{
script[i] = -1; // miss
}
else
{
// Zipfian hit
if (rng.NextDouble() < 0.8)
{
script[i] = rng.Next(0, hotSetSize);
}
else
{
script[i] = rng.Next(hotSetSize, keyCount);
}
}
}
return script;
}
/// <summary> Fisher-Yates shuffle. </summary>
private static void Shuffle(
int[] array,
Random rng
)
{
for (int i = array.Length - 1; i > 0; i--)
{
int j = rng.Next(0, i + 1);
(array[i], array[j]) = (array[j], array[i]);
}
}
} }
} }
+11 -39
View File
@@ -2,8 +2,8 @@
// ----------------------------------------------------------------------- // -----------------------------------------------------------------------
// file="SwissTable" // file="SwissTable"
// Project: StgSharp // Project: StgSharp
// AuthorGroup: Nitload // AuthorGroup: Nitload Space
// Copyright (c) Nitload. All rights reserved. // Copyright (c) Nitload Space. All rights reserved.
// //
// Permission is hereby granted, free of charge, to any person obtaining a copy // Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal // of this software and associated documentation files (the "Software"), to deal
@@ -43,14 +43,12 @@ namespace StgSharp.Collections
private const int BucketCount = 1 << EntryMaskWidth; private const int BucketCount = 1 << EntryMaskWidth;
private const int BucketSize = 16; private const int BucketSize = 16;
private const uint CrcMagic = 0xffff9961; // Magic number for CRC32C, used in hash computation private const uint CrcMagic = 0xffff9961; // Magic number for CRC32C, used in hash computation
private const int EntryMaskWidth = 16; // 65536 entries total, 16 per bucket private const int EntryMaskWidth = 10; // 1024 entries total, 16 per bucket
public const int MaxCapacity = BucketCount * BucketSize; // 256 entries per bucket, 1024 buckets public const int MaxCapacity = BucketCount * BucketSize; // 256 entries per bucket, 1024 buckets
private readonly Entry* _entries; private readonly Entry* _entries;
private SwissTable( private SwissTable(Entry* buffer)
Entry* buffer
)
{ {
_entries = buffer; _entries = buffer;
} }
@@ -66,11 +64,7 @@ namespace StgSharp.Collections
return new SwissTable(buffer); return new SwissTable(buffer);
} }
public bool TryAddOrSet( public bool TryAddOrSet(nint key, nint value, out bool isNewKey)
nint key,
nint value,
out bool isNewKey
)
{ {
uint hash = BitOperations.Crc32C(CrcMagic, (ulong)key); uint hash = BitOperations.Crc32C(CrcMagic, (ulong)key);
ushort entry = (ushort)(hash & (BucketCount - 1)); ushort entry = (ushort)(hash & (BucketCount - 1));
@@ -78,10 +72,7 @@ namespace StgSharp.Collections
return IBucketScanner.Current.TrySet(key, hash, bucket, value, out isNewKey); return IBucketScanner.Current.TrySet(key, hash, bucket, value, out isNewKey);
} }
public bool TryGet( public bool TryGet(nint key, out nint value)
nint key,
out nint value
)
{ {
uint hash = BitOperations.Crc32C(CrcMagic, (ulong)key); uint hash = BitOperations.Crc32C(CrcMagic, (ulong)key);
ushort entry = (ushort)(hash & (BucketCount - 1)); ushort entry = (ushort)(hash & (BucketCount - 1));
@@ -96,10 +87,7 @@ namespace StgSharp.Collections
*/ */
} }
public bool TryRemove( public bool TryRemove(nint key, out nint value)
nint key,
out nint value
)
{ {
uint hash = BitOperations.Crc32C(CrcMagic, (ulong)key); uint hash = BitOperations.Crc32C(CrcMagic, (ulong)key);
ushort entry = (ushort)(hash & (BucketCount - 1)); ushort entry = (ushort)(hash & (BucketCount - 1));
@@ -134,27 +122,11 @@ namespace StgSharp.Collections
static IBucketScanner Current { get; } = Create(); static IBucketScanner Current { get; } = Create();
bool TryFind( bool TryFind(nint key, uint Hash, Bucket* bucket, out nint value);
nint key,
uint Hash,
Bucket* bucket,
out nint value
);
unsafe bool TryRemove( unsafe bool TryRemove(nint key, uint hash, Bucket* bucket, out nint value);
nint key,
uint hash,
Bucket* bucket,
out nint value
);
bool TrySet( bool TrySet(nint key, uint hash, Bucket* bucket, nint value, out bool isNewKey);
nint key,
uint hash,
Bucket* bucket,
nint value,
out bool isNewKey
);
private static IBucketScanner Create() private static IBucketScanner Create()
{ {
@@ -197,4 +169,4 @@ namespace StgSharp.Collections
} }
} }
} }
@@ -0,0 +1,59 @@
//-----------------------------------------------------------------------
// -----------------------------------------------------------------------
// file="L4"
// Project: StgSharp
// AuthorGroup: Nitload Space
// Copyright (c) Nitload Space. All rights reserved.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
//
// -----------------------------------------------------------------------
// -----------------------------------------------------------------------
using StgSharp.Collections;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace StgSharp.HighPerformance.Memory
{
public unsafe class L4
{
private readonly byte* _buffer;
private readonly SwissTable _map;
public nint MapMemory(nint address)
{
if (_map.TryGet(address, out nint ptr))
{
return ptr;
} else
{
/*
* register a request for memory mapping,
* and return a pointer to the mapped memory.
*/
return 0;
}
}
}
}
@@ -77,8 +77,8 @@ L4 缓存器是一个纯软件实现的**线程本地数据缓存层**,
| 参数 | 值 | 说明 | | 参数 | 值 | 说明 |
|-------------------|-----------------------|-----------------------------------| |-------------------|-----------------------|-----------------------------------|
| 缓存区总容量 | 5-10 MB | 线程本地连续内存 | | 缓存区总容量 | 5-10 MB | 线程本地连续内存 |
| 缓存行大小 | 1024 Bytes | = 8 个 `double MAT_KERNEL` 的大小 | | 缓存行大小 | 8192 Bytes | = 64 个 `double MAT_KERNEL` 的大小 |
| 映射表类型 | Swiss Table | 1024 桶 × 256 槽,SIMD 加速 | | 映射表类型 | Swiss Table | 65536 桶 × 16 槽,SIMD 加速 |
| 缓存行存储池 | Slab Allocator | 非并发、固定容量、不自动扩容 | | 缓存行存储池 | Slab Allocator | 非并发、固定容量、不自动扩容 |
| 逐出策略 | 4 级热度环形链表 | 基于访问频率的近似 LFU | | 逐出策略 | 4 级热度环形链表 | 基于访问频率的近似 LFU |
| 写回策略 | 无(只读缓存) | 逐出时直接丢弃,不写回远端 | | 写回策略 | 无(只读缓存) | 逐出时直接丢弃,不写回远端 |