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feat: Update bench + core/root -> latest dev Zig ver

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Triex 2025-06-06 15:55:07 +10:00
parent 24b5fcfd02
commit b1c1f2c07f
2 changed files with 19 additions and 15 deletions
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33
experimental/bench/main.zig
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@ -6,6 +6,9 @@ const deepseek_core = @import("deepseek_core");
const cpu_backend = @import("cpu_backend");
const print = std.debug.print;
// Import Shape from deepseek_core
const Shape = deepseek_core.Shape;
const BenchmarkResult = struct {
name: []const u8,
iterations: u32,
@ -34,15 +37,15 @@ pub fn main() !void {
defer _ = gpa.deinit();
const allocator = gpa.allocator();
print("🚀 DeepZig V3 Performance Benchmarks\n");
print("==========================================\n\n");
print("🚀 DeepZig V3 Performance Benchmarks\n", .{});
print("==========================================\n\n", .{});
// Initialize backends
const cpu_backend_instance = try cpu_backend.init(allocator);
var cpu_backend_instance = try cpu_backend.init(allocator);
defer cpu_backend_instance.deinit();
print("Backend: CPU (SIMD optimized)\n");
print("Architecture: {s}\n", @tagName(@import("builtin").cpu.arch));
print("Backend: CPU (SIMD optimized)\n", .{});
print("Architecture: {s}\n", .{@tagName(@import("builtin").cpu.arch)});
print("Thread count: {d}\n\n", .{std.Thread.getCpuCount() catch 4});
// Run benchmarks
@ -62,22 +65,22 @@ pub fn main() !void {
try results.append(try benchmarkMemoryBandwidth(allocator));
// Print results
print("Benchmark Results:\n");
print("------------------\n");
print("Operation | Iterations | Avg Time | Operations/s | Memory\n");
print("-------------------------------|------------|-----------|--------------|-------\n");
print("Benchmark Results:\n", .{});
print("------------------\n", .{});
print("Operation | Iterations | Avg Time | Operations/s | Memory\n", .{});
print("-------------------------------|------------|-----------|--------------|-------\n", .{});
for (results.items) |result| {
print("{}\n", .{result});
}
print("\n🎯 Benchmark completed!\n");
print("\n🎯 Benchmark completed!\n", .{});
}
/// Benchmark tensor creation and memory allocation
fn benchmarkTensorCreation(allocator: std.mem.Allocator) !BenchmarkResult {
const iterations = 1000;
const shape = deepseek_core.Tensor.Shape.init(&[_]u32{ 1024, 1024 });
const shape = Shape.init(&[_]u32{ 1024, 1024 });
const start_time = std.time.nanoTimestamp();
@ -103,7 +106,7 @@ fn benchmarkTensorCreation(allocator: std.mem.Allocator) !BenchmarkResult {
/// Benchmark SIMD-optimized tensor addition
fn benchmarkTensorAddition(allocator: std.mem.Allocator) !BenchmarkResult {
const iterations = 100;
const shape = deepseek_core.Tensor.Shape.init(&[_]u32{ 4096, 1024 });
const shape = Shape.init(&[_]u32{ 4096, 1024 });
var a = try deepseek_core.Tensor.ones(allocator, shape, .f32);
defer a.deinit();
@ -145,9 +148,9 @@ fn benchmarkMatrixMultiplication(allocator: std.mem.Allocator) !BenchmarkResult
const k = 1024;
const n = 1024;
const a_shape = deepseek_core.Tensor.Shape.init(&[_]u32{ m, k });
const b_shape = deepseek_core.Tensor.Shape.init(&[_]u32{ k, n });
const c_shape = deepseek_core.Tensor.Shape.init(&[_]u32{ m, n });
const a_shape = Shape.init(&[_]u32{ m, k });
const b_shape = Shape.init(&[_]u32{ k, n });
const c_shape = Shape.init(&[_]u32{ m, n });
var a = try deepseek_core.Tensor.ones(allocator, a_shape, .f32);
defer a.deinit();

1
experimental/src/core/root.zig
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@ -5,6 +5,7 @@ const std = @import("std");
// Core components
pub const Tensor = @import("tensor.zig").Tensor;
pub const Shape = @import("tensor.zig").Shape;
pub const Model = @import("model.zig").Model;
pub const Transformer = @import("transformer.zig").Transformer;
pub const Attention = @import("attention.zig").Attention;